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Theses and Dissertations 


1. Thesis and Dissertation Collection, all items 


1981-03 

An experiment in voice data entry for imagery 
interpretation reporting. 

Jay, Gregory T. 

Monterey, California. Naval Postgraduate School 


http://hdl.handle.net/10945/20526 


This pubiication is a work of the U.S. Government as defined in Titie 17, United 
States Code, Section 101. Copyright protection is not avaiiabie for this work in the 
United States. 

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THESIS 

AN EXPERIMENT IN VOICE DATA ENTRY FOR 
IMAGERY INTERPRETATION REPORTING 

by 

Gregory T. Jay 
March 1981 

Thesis Advisor G. K. Poock 

Approved for public release; distribution unlimited. 





SCCURITY CLASSlfICATION Of THIS PAGE (Wh9t% Dmtm entmrmd) 


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2. GOVT ACCESSION NO. 

3. PECiPiCNT'S CAT ALOG NUMBER 

4. TITLE fand 

An Experiment in Voice Data Entry for 

Imagery Interpretation Reporting 

5. TYPE Of REPORT ft PERIOD COVERED 

Master's Thesis; March 1981 

S. PERfORMIMG ORG. REPORT NUMBER 

7. AUTHOnr*; 

Gregory T. Jay 

ft. CONTRACT OR GRANT NUMBER|«> 

f. fCNfONMING ONOANIZATION NAME ANO AOONEtS 

Naval Postgraduate School 

Monterey, California 93940 

10. PROGRAM ELEMENT. PROJECT TASK 

AREA ft WORK UNIT NUMBERS 

1 1. CONTMOLLINO orrice NAME ANO AOONCSS 

Naval Postgraduate School 

Monterey, California 93940 

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March 1981 

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Approved for public release; distribution unlimited. 

17. OlSTfiEUTlON STATEMENT (ol th9 mtfrmd In Block 30, II dilloront Ifom Rmport) 

It. SUPfLEMENTANY NOTES 

19. KEY WOPOt iConlInu* on rororto old# II noeooooiT dnd Idonillf ky klotk t%iMmbmr) 

Automatic Speech Recognition 

Voice Data Entry 

Imagery Interpretation 

Intel 1igence 

Experiment 

20. ABSTPACT |Conllm«o on rovoroo oldo II nocooonrr md Idonlllp ftp ftlocft mnoftorj 

This thesis investigated the feasibility of voice data entry for imagery 
intelligence order of battle reporting. Time, accuracy, and efficiency were 
measured for 20 subjects in an experiment physically simulating the use of a 
light table, optics, and an interactive computer system for reporting. A 
Threshold Technology Inc. T600 voice recognition system was used for a large, 
unstructured vocabulary (255 words) of unclassified Soviet/Warsaw Pact 
equipment names, alphanumerics, and editing commands. The T600 recognition 


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accuracy for this experiment was 97.0^ without rejects, and 95.5% with 
rejects. 

Buffered voice and unbuffered voice modes of the T600 were evaluated 
with typing: buffered voice was 58% faster, and unbuffered voice 41% faster 
than typing. Voice was also found to be as accurate as typing for writing 
short order of battle reports. Finally, subjects preferred voice for 
several criteria evaluated before and after the experiment. 


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rcvad for pi-llic release; aisir ilut ioa uLiinlted. 


An Ixperiment in Voice Date Zntry for 
Imagery Interpretation Repcrtins- 


by 


Sregor/ T. Jay 

Captain, United States Air Force 
2.S. Id., ^'iemi University of Ohio, 1970 
r'l.S. Fd., Miami University of Ohic, 1971 


Submitted in partial fulfillment of the 
requirements for the degree of 


MASTER OF SCI2NCE IN SYSTEMS TECHNOLOGY - C3 

from the 

NAVAL PCSTGRAUUATE SCKCCL 
March 19S1 







ABSTRACT 




This thesis investigated the feasibility of voice data 
entry for imagery intelligence order of battle reporting. 
Time, accuracy, and efficiency were measured for 20 subjects 
in an experiment physically simulating the use of a light 
table, optics, and an interactive computer system for 
reporting. A Threshold Technology Inc. T600 voice 
recognition system, was used for a large, unstructured 
vocabulary (255 words) of unclassified Scviet/Warsaw Pact 
equipment names, alphanumerics, and editing commands. The 
Te00 reccgniton accuracy for this experiment was 97.0% 
without rejects, and 95.5% with rejects. 

Buffered voice and unbuffered voice modes of the T600 
were evaluated with typing: buffered voice was 58% faster, 
and unbuffered vcice 41% faster than typing. Voice was alsc 
found to be as accurate as typing for writing short 
order of battle reports. Finally, subjects preferred 
voice for several criteria evaluated before and after the 
experiment. 


4 


TAPLS OF CONTINTS 


I. BACKGROUND LIADING TO FXPZRIMENTATION - 

A. INTRODUCTION - 

B. IMAGERY INTERPRETATION REPORTING SYSTEMS - 

1. functicns - 

2. Examples of Imagery Interpretation 

Reporting Systems - 

3. Requirement for Voice Data Entry - 

C. AUTOMATIC SPEECH RECOGNITION - 

1. Overview - 

2. Value of Speech Recognition Systems - 

3. Military Research and Applications - 

D. SUMMARY - 

II. DESCRIPTION OF THE EXPERIMENT - 

A. OBJECTIVES AND CONSTRAINTS - 

B. SUBJECTS - 

C. EQUIPMENT - 

1. Voice Recognition System - 

2. Tachistoscope - 

3. Scenario Cards and Vocabulary - 

4. Interactive Computer System: ARPANET - 

D. SUBJECT PREPARATION - 

1. Te00 Vocabulary Training - 

2. Typing Test - 


12 

12 

17 

17 

19 

28 

29 

29 

32 

36 

39 

41 

41 

42 

43 

43 

4c 

52 

54 

58 

58 

60 


5 























4 


Subjective Questicnnaire and Data Sheet 


61 


'Z 


Z. IXPZRIMZMAL FHOCZDURZ - 52 

J. DZPZNDINT VARIABLZS - 66 

G. EYPOTEZSZS- 68 

1. Hypotheses Regarding Time- 68 

2. Hypotheses P.egardiag Accuracy- 56 

3. Hypotheses P.egardiag Efficiency- 59 

4. Hypotheses P.egardiag T600 P.eccgniticn 

Accuracy without P.ejects- 69 

5. Hypotheses Regarding T600 Recognition 

Accuracy with Rejects- 70 

6. Hypothesis Regarding Subject Attitudes — 70 


H . 
I . 


ZXPZRIMZNTAL DESIGN - 

RESULTS - 

1. Results for Reporting Time - 

2. Results for Reporting Accuracy - 

3. Results for Reporting Efficiency - 

4. Results for T600 Recognition Accuracy - 

5. Results for Subject Attitudes - 


70 

72 

72 


80 

84 


86 


III. DISCUSSION 


90 


GENERAL 


90 


3. RECOKt^ENDATIONS 

1. Research 

2. Applications 

C. CONCLUSIONS - 


94 


95 


6 

















































APPENDIX A: 

APPENDIX B: 
APPENDIX C : 
APPENDIX D; 
APPENDIX S; 
APPENDIX f: 
APPENDIX G; 
APPENDIX H: 
APPENDIX I: 


USSR/\vARSAW PACT ORDER CF BATTLE (OB) 


VOCABULARY - 96 

SCENARIO CARDS - 102 

T600 TRAINING INSTRUCTIONS - 120 

TYPING TEST-123 

PRS/POST SUBJECTIVE QUESTIONNAIRE - 125 

SUBJECT DATA SHEET -128 

INSTRUCTIONS BRIEFED TO SUBJECTS - 129 


VOCABULARY '*CRDS MISRSCCGNIZED OR REJECTED 135 
RESULTS FOR PRE/POST SUBJECTIVE 
QUESTIONNAIRE - 146 


LIST OF REFERENCES -150 

INITIAL DISTRIBUTION LIST - 152 


7 




























































LIST OF TABLES 


I. I^SAN REPOHTING TIKE- 74 

II. ANALYSIS OF VARIANCE FOR REPORTING TIKE 

(SECONDS) - 75 

III. KEAN REPORTING ACCURACY (%) - 76 

IV. ANALYSIS OF VARIANCE FOR ARCS IN-TRANSFORMED 

REPORTING ACCURACY - 79 

V. MEAN REPORTING EFFICIENCY (%) - 61 

VI. ANALYSIS OF VARIANCE FOR ARCS IN-TRANSFORMED 

REPORTING EFFICIENCY - 82 

VII. MEAN T600 RECOGNITION ACCURACY (%) 

WITHOUT REJECTS - 85 

VIII. MEAN T600 RECOGNITION ACCURACY (%) 

WITH REJECTS- 85 

IX. ANALYSIS OF VARIANCE FOR ARCS IN-TRANSFORMED 

T600 RECOGNITION ACCURACY WITHOUT REJECTS - 86 

X. ANALYSIS OF VARIANCE FOR ARCS IN-TRANSFORMED 

T600 RECOGNITION ACCURACY WITH REJECTS - 87 


8 














LIST Cf FIGURES 


1. Basic Coirnand and Control Model- 15 

2. CATIS Ixagery Exploitation Support - 21 

3. TIPI IiT;agery Interpretation Systerr (IIS)- 22 

4. TIPI Manual Radar Reconnaissance Exploitation 

Systerr (MARPES) - 23 

5. QSR Reconnaissance Reporting Facility (RRF) - 25 

6. Compass Previev/ Digital Exploitation System- 26 


7. Threshold Technology Inc., T602 Voice Recognition 


System with Ann Arbor Terminal (facing left) and 

Keyboard, and Shure SM-10 Microphone - 45 

6. Tachistoscope Interfaced to Ann Arbor Display and 

Motorized Card Presentation Peripheral - 49 

9. Tachistoscope Viewport Used to Simulate Optics 

and Light Table- 51 

10. Sample Scenario Cards - 53 

11. ARPANET MAP- 56 

12. ADM Terminal Attached to ISI Computer via the 

ARPANET- 57 

13. Monitor Station- 59 


14. CB Reporting Format Eased on Cards in Figure 10 — 64 


9 















Concept\;a] ijesi,?n of the Siperinent 


71 


16. 

17. 

18. 


yeaa Reporting; Time by Data Entry Mode- 

Mean Reporting: Time by Trial - 

Mean Reporting Efficiency by Data Entry Mode 


76 

77 
63 























ACSNO’A'LEDGSf^iNTS 


I happily take this opportunity to express well-deserved 
thanks to the many kind people who supported rte in this 
thesis research. Special thanks to Professor Gary Poock, an 
"ideal advisor," to Professor Bill Mcroney, my patient and 
helpful second reader, and to Mr. Paul Sparks who faithfully 
set up the equipment and graciously assisted me whenever 
necessary. 

I also thank all the people who participated in the 
experiment, unselfishly dedicating approximately eight hours 
of their free time to help further voice research. 

host importantly, warm thanks to my wife Joy, and our 
children Heather, 2ric, and Sam who stood by me physically 
and spiritually through the seemingly endless hours of 
thesis experimentation and writing. Finally, as the 
psalmist wrote: 

I give thanks to the Lord, for He is good? for His 
lovingkindness is everlasting [Psalm 11S:29]. 


11 


I. BACKGROUND LEADING TO EXPERIMENTATION 


A. INTRODUCTION 

This thesis investigates the potential application of 
automatic speech recognition (ASP.) technology to military 
imagery interpretation reporting. It stems from the 
author's background in three areas: imagery interpretation, 
Intelligence Data Handling Systems (IDES), and recent 
exposure to the benefits of voice data entry as an 
alternative modality for interacting with m^achines, 
especially computers. 

The need for the thesis arises from two areas: the need 
to evaluate and advance current ASH technology without major 
redesign of systems* and the need for faster, reliable 
reporting systems for the intelligence community. Dr. Wayne 
Lea and Dr. Gary Poock called for the evaluation of state- 
of-the-art ASR equipment, specifically, to evaluate input 
modalities, e.g. voice versus typing [Refs. 1 and 2]. The 
intelligence community is continually seeking ways to 
improve performance of imagery sensors and exploitation and 
reporting systems, and is very interested in ways of 
reducing costs while improving the quality of intelligence 
to tactical and strategic users. 

The Soviet Union and the Warsaw Pact countries are 
expected to employ mass, mobility, and surprise tactics in 


12 



















aa/ future European attack scenario on our North Atlantic 
Treaty Organization (NATO) Allies. The speed and ran^je of 
rrodern weaponry leave little or no room for iristakes in 
responding to crisis situations. Decision-making in minutes 
or even seconds is a requirement today, and is likely to be 
more critical in the future with the increased use of 
microelectronic components for sensor and weapons control, 
and faster, more redundant, survivable, and interoperable 
communications facilities. National Command Authorities, 
U.S. Strategic and Tactical Forces, and NATO Theater Forces 
must have accurate, timely, and complete indications and 
warning (I&W) intelligence of the enemy's real intentions 
and capabilities. Once hostilities begin, with today's 
warfighting technology, military commanders will require 
near-real-time (NRT) combat information to enable them to 
provide effective command and control of their forces to 
counter the enemy. 

Globally, intelligence must be available for 
national security decisions regarding appropriate 
responses to international terrorism and the unwarranted 
intervention of foreign powers into the affairs of 
other nations. Additionally, intelligence is 
required for long-range planning estimates to support the 
acquisition of the best possible mix of forces to 
meet mission requirements in support of basic U.S. 
policy and objectives. Finally, intelligence must 


13 


continually support Strategic Nuclear Commend and Control 
forces which rust always be at a sufficient state of 
readiness to provide nuclear deterrence. 

The following basic commend and control model in Figure 
1 was adapted frcm the work of Dr. o^cel Lawson, Technical 
Director, Naval Electronics Systems Command [Hef. 3]. It is 
shown here to illustrate the importance of the intelligence 
process in providing support to command and control of 
forces in war and peace. Note that it does little good to 
provide better sensors without also improving the ability to 
compare the information derived with objectives and 
historical information in conjunction with intelligence 
analysts, inherent in the "compare” process. In the 
reconnaissance area, imiagery exploitation and reporting 
would fall under the "compare" function of the system, and 
as such can be a major information "bottleneck" if not 
capable of effectively processing the sensor output to meet 
the information needs of the decision-maker. 


14 


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Figure 1. Basic Command and Control Model 
Regarding the central importance of the command and 
control process, Dr. Lawson states, 


...the central prohlem of command control is producing 
an up-to-date geographic display of the location of 
’’things." Besides purely the location of things he [the 
commander] needs to know what [the] things are, what is 
their identity, or who do they Belong to and what is 
their status. 


Imagery is a key source of such information, and is thus a 
major contrihutor to the comm,and and control process. 

Automated imagery interpretation reporting systems have 
been employed for strategic and theater support for over 10 
years, and new systems which include exploitation aids are 
being deployed to tactical units now. They have 


15 





significantly reduced the tine tc exploit and report all 
types of imagery intelligence. However, the man-machine 
interface research and development of these systems must 
continue to meet future challenges facing the intelligence 
community. Significant volumes of imagery intelligence will 
be available from NRT digital imagery sensors in the future, 
and the best possible man-machine interface must be sought 
to effectively exploit IS’*, order of battle, targeting, and 
damage assessment intelligence available from imagery. 

Reporting speed and accuracy, manpower reducticns,and 
increased throughput are worthy design goals for new or 
improved imagery exploitation and reporting systems. Voice 
data entry is one newly evolving technology that offers 
significant potential toward these goals. Dr. Wayne Lea, in 
the introduction to his book Trends in Speech Recognition, 
1980, said: 

Speech input seems to offer a truly natural mode of 
human-machine communication that, if attainable in a 
cost-effective way, would be unsurpassed in making 
computers and other mechanical devices truly cooperative 
servants of mankind, rather than increasing the demands 
on the human to adapt to the machine [Ref. 4]. 

The next section briefly overviews the functions of 
imagery reporting systems, provides some examples of 
systems for today and tomorrow, and mentions some specific 
requirements which lead to the desirability of voice 
data entry for imagery intelligence reporting. 


16 





B. IMAGERY INTERPRETATION REPORTING SYSTEMS 


1. Func tions 

A milixary imagery interpretation system basically 
functions to provide support for first, second, and third 
phase exploitation of multi-sensor imagery in response to 
tasking from parent or outside user organizations. These 
phases represent three levels of depth of imagery analysis 
in accordance with Defense Intelligence Agency (DIA) 
standard reporting procedures, data elements, and 
requirements. 

First and second phase reports represent the hulk of 
the work, and are called Initial/Supplementary Photo 
Interpretation Reports (IPIRs/SUPIRs). The IPIR m:ay he 
thought of as a quick, concise response to time-sensitive 
requirements. It .is often followed hy the SUFIR, which 
represents a more detailed and thorough exploitation effort. 
Third phase reporting is the most detailed, and includes 
special analyses and reporting of selected installations of 
specific interest to users of imagery products. 

Such reporting standards and systems grew out of 
requirements forced hy large increases in the volume of 
available imagery during the sixties. During the sixties, 
the volume of imagery exceeded the exploitation capabilities 
hy a factor of five to ten [Ref. 5]. This drove the 
development of a variety of imagery exploitation and 
reporting systems which came into operation in the 


17 




seventies, and forced standards for reporting cn the imagery 
intelligence corr.muni ty as a whole. These developments 
permitted the sharing of imagery intelligence via magnetic 
tape files and bvlk data transfers over communications 
circuits. It also facilitated the integration of imagery 
intelligence intc more general data bases, and enhanced the 
corporate memory" of intelligence units, since interpreters 
often kept installation data in small personal files, net 
easily accessed by others. With better data bases, 
exploitation was enhanced and duplication of effort was 
reduced. 

Today, imagery exploitation systems are located 
worldwide in support cf U.S. military commanders. The focus 
now is on providing more integrated data bases, which are 
optimally dynamic, complete, and timely. Kulti-scurce 
imagery reports may be telecommunicated to and from many of 
the sites, and distributed tc users with a valid 
requirement. Integrated data bases will afford producers 
and users with more responsive, coordinated information in 
time of need. 

Imagery systems range from national level to 
tactical reconnaissance squadron level systems. They have 
become increasingly capable of supporting many tasks 
associated with exploitation and reporting: responding tc 
tasking transmitted over telecommunications networks? 
managing interpretation hardware, software, and data base 


18 






resources; exploiting the imagery to include making 
measurements on the imagery, correlating imagery with maps, 
composing reports, editing them, and other support 
functions; disseminating reports; and automatic screening 
and updating cf local imagery and multi-source data bases. 

2. Examples of Imagery Interpretation Reporting Systems 

The DIA uses the Automated Imagery Related 
Exploitation System (aIRES), modeled after the PACER system 
used by the Strategic Air Command's 544th Aerospace 
Reconnaissance Technical Wing. PACER means Program Assisted 


Console 

Evaluation 

and Review, 

and oonsists of a 

dual 

Honeywell 

6080 

based computer 

system 

and UNIVAC 

1652 

consoles 


supporting the interpretation 

process . 

Both 

systems 

support a 

wide variety of 

analyst 

functions. 



A 

s ys t em 

developed and 

installed in the 

late 


seventies for theater and tactical user support is the 
Computer Assisted Tactical Information System (CATIS). This 
system is used by fixed-site, imagery exploitation units in 
the Pacific Air Forces (PACAE), the Tactical Air Command 
(TAC), the Fleet Intelligence Center for Europe and the 
Atlantic (FICEURLANT), the United States Air Forces in 
Europe (USAFE), and the training site in Air Training 
Command (ATC). The imagery exploitation support provided by 
CATIS may be viewed in Figure 2. 

To provide highly mobile support, the Tactical 
Information Processing and Interpretation, Imagery 


19 



Interpretation System (TIPI IIS) was developed, and is being 
deployed to Air force, Marine, and Army tactical 
reconnaissance support units worldwide. The photo 
interpretation console of the TIPI IIS may be viewed in 
figure 3, displaying a great deal of modular, ruggedized 
support equipment for imagery interpretation reporting and 
communications. This system provides mobile automation at 
the squadron level, not previously available. For example, 
an interpreter can use a cursor in the light table to make 
rapid, accurate measurements of objects such as bridges, 
runways, and storage tanks and store the answer on an 
electronic scratch pad for later insertion into a report. 
Reports are filled in quickly, using a fill-in-the-blank 
online report composer. They may then be edited by a 
supervisor, and distributed over secure communications 
links. 

To perform side-looking airborne radar (SLAR) 
exploitation and reporting the TIPI Manual Radar 
Reconnaissance Exploitation System (MARRES) was 
developed, but with a different ccnscle (figure 4). This 
system provides special readout of radar imagery that may be 
used in good or bad weather, and is useful for discovering 
enemy force movements in inclement weather, such as that 
found in Europe. Unique man-machine systems have been 


20 














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figure 3. TIPI Imagery Interpretation Syste- (IIS) 
(Courtesy of Texas Instruments, Inc.) 


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provided to assist in providing detection of changes in the 
landscape or order of battle. 

New NRT digital imagery reconnaissance sensors, 
such as foward-looking infrared imagery (FLIR), Synthetic 
Aperature Radar \SAR), or other types of imagery 
which can he supported by sensors on tactical aircraft 
will result in increased NRT imagery. Exploitation 
system.s to support the sensors must be developed to provide 
the additional support required. The Air Force has 
initiated advanced developmental models to prepare for 
such a requirement. 

One system is the Reconnaissance Reporting 
Facility developed to support the Quick Strike 
Reconnaissance concept whereby the reporting facility would 
receive NRT hardcopy and softcopy (digital) imagery from 
reconnaissance aircraft over the forward edge of the battle 
area. When advancing enemy forces posed themselves as 
targets of opportunity, imagery reports would notify the 
strike center to order nearby airborne loitering 
aircraft to destroy the target. Figure 5, top and 
bottom, gives views of the shelter developed to test 
the NRT reporting concept. 


24 

















Figure 5. QSR Reccnnaissance Reporting 
(Courtesy of Texas Instruir.ents, 


Facility 
Inc.) 


(RRF) 


25 



le 


Fi^vire 6. Compass Preview 
Digital Exploitation System 
(Courtesy of Northrop Corporation) 






























The RRF contains computers, communications, and both 
hardcopy and softcopy imagery exploitation and reporting 
stations. Used during exploitation of a target-rich 
wartime environment, this facility would pose a 
challenging work environment for the best of interpreters 
and supervisors. Efforts to optimize the man-computer 
interface could only result in improved responsiveness and 
greater system capability. 

Another system, for strategic use, is the Compass 
Preview digital imagery exploitation system shown in Figure 
6. For the first time, interpreters will be able to view 
stereo images without the aid of a light table, hardcopy 
imagery, or a stereoscope. The interpreter can use computer 
support to enhance the image to improve its interpretability 
in terms of scale, contrast, sharpness, and other image 
qualities. Simultaneously, historical data base information 
and reporting formats are available for reporting what is 
seen on the image and correlated with other data. 
Measurements may also be made using a Joystick and cursor. 

The imagery systems discussed represent a large leap 
forward in imagery intelligence since the late sixties. The 
results from current systems such as PACER and CATIS are 
encouraging with 3:1 and 12:1 increases in output as 
compared to their predecessors, less duplication of effort, 
increased validity of reporting, and most importantly, 
better responsiveness to specific user questions. 


27 


Imagery reporting systems are quite 
sophisticated, having incorporated not only state-of- 
the-art exploitation techniques, tut others as 
well from computer, communications, and other 
intelligence disciplines. Significant skill and 
training are required to operate them effectively. 
Interpreters are not trained typists, and thus their speed 
may slow the reporting process. Additionally, they may 
nave an inherent fear of working- with computers. 
Continuing attention must he given to improving the 
man-machine interface to optimize the system product: 
complete, accurate, and timely imagery intelligence. Though 
not a panacea, voice data entry may be part of the solution 
for improving the imagery interpretation systems, by 
improving man's interface with the machine, and making 
optimal use of man's skills as an image analyst. 

3. Requirement for Voice Data Zntry 

During the author's recent assignment at the Armed 
Forces Air Intelligence Training Center, he was responsible 
for managing the initial development of the TIPI IIS 
Operator and Supervisor Courses. As he observed 
interpreters training on the prototype, it was often 
apparent that they were deficient in typing skills. It was 
painfully obvious that the multi-million dollar IIS would 
not produce reports any faster than the few words-per-minute 
of the "hunt and peck" typist. Certainly, with practice 


26 



individuals may improve their typing speed and accuracy as 
they adapt to a system, hut as we have seen, the trend is 
toward faster reporting, and somehow the problem of data 
entry must he attacked or critical resources will he wasted 
on systems limited by the the mac-in-the-1oop. 

One simple and effective way may he to conduct 
typing classes to improve interaction with the computer. In 
fact, online routines for teaching better typing could he 
developed to improve the interpreters' skills between 
missions. Another way may be to use voice data entry, which 
offers a great potential beyond even the fastest typists for 
data entry, should be easier and faster to train, and could 
be used in conjunction with typing, function keys, or a 
variety of other input modalities. 

G. AUTOMATIC SP3ICH R2C0GNITICN 
1. Overview 

Automatic Speech Recognition (ASR) is no longer a 
dream of the future, hut a technology being applied around 
the world by people who use machines, allowing effective 
machine control and data entry into computers. ASR is not 
without problems or limitations however, and must he 
carefully examined before trying to apply it. Human factors 
must he studied and tailored to the application to allow ASR 
to have the appropriate im.pact it affords. Failure to 
attend to operator considerations such as microphone 


29 





4*ii 






rrounting, recognition accuracy, error correction, response 
time and delay, feedback and prompting, stability of 
reference data, and training procedures can have 
catastrophic effects on system performance for both the 
voice system and the system it aids [Ref. 7], 

The ultimate goal for speech recognition 
science is to develop "speech understanding systems" 
which give the appropriate response to the user's 
request, and do not just recognize tne elements of speech or 
words and phrases [Ref. 8]. Admittedly, the technology is 
not that far along, but many applications dc not need cr 
cannot afford the ideal speech system. The question that 
must be asked now is "what applications can be 
accomplished in a more cost-effective manner witn voice 
recognition systems that are available now or will be 
available within the next few years?" 

Speech scientists have been working on ASR for about 
28 years. Commercially available speech recognizers became 
available in 1972 with Scope Slectrcnics, Inc. and Threshold 
Technology Inc. delivering quality systems which achieved 
significant results under a variety of conditions. In 
general, recognition accuracy scores from 99.0% to 99.9% 
accuracy have been achieved in laboratory conditions of no 
noise, adequate talker training, and consistent talking 
habits. Field testing, however has usually achieved results 
in the neighborhood of 97% recognition accuracy, generally 


30 


as a result cf high background noises or speaking to the 
system in a manner different than the way the system was 
trained initially. 

All ASR systems fall into either of two 
categories: continuous (connected) or isolated (discrete) 
speech systems [Ref. 9]. Continuous speech systems work on 
the extraction of information from strings of words 
that may be run together in natural speech in the form of 
strings of digits, phrases, or sentences. Isolated-word 
recognizers require that a short minimum-duration pause 
be inserted between digits, words or phrases which must be 
spoken within a given period of time, e.g. two seconds. 

These isolated-word recognizers are more prevalent 
today as they are less expensive, more accurate, work in 
real-time, ana are more readily available. Continuous 
speech systems, however, may be available within the next 
few years offering 250 word vocabularies and recognition 
in real-time at a reasonable price. Centinucus speech 
systems, in the upper end of the cost spectrum, are 
approximately $100,000. Eigh quality isolated-word speech 
recognizers normally cost in the tens of thousands of 
dollars today? however, a few companies are also introducing 
systems on the market for a few thousand dollars that 
can recognize vocabularies of about 250 words with 
recognition accuracies of 97^ or better, according to 
Dr.Poock, who intends to compare such systems at NFS for 


31 


command and control applications. At the bottom end 
of the cost spectrum, hobby systems are currently available 
for a few hundred dollars. 

Dr. Lea, well recognized for his work in speech science 
at the University of Southern California and the Speech 
Communication Research Laboratory said this about the future 
of speech recognition technology: 


The next ten years or more would seem to offer a growing 
spectrum of available devices, ranging from very low 
cost isolated word recognizers, through digit string 
recognizers, recognizers of strictly formatted word 
se«iuences, task-restricted speech understanding systems, 
and more powerful research systems for continuous speech 
recognition. All such systems will take advantage of 
low-cost miniaturization hardware that puts speech 
recognizers within the reach of most potential users... 
User acceptance of voice input will approach the 
"matter-of-fact" attitudes now prevalent with limited 
keyboard entry, even though full versatility and 
"habitability" of input languages will not have been 
attained to any major degree... Despite all these 
advances, we will be far from the science fiction image 
of fully versatile voice interaction with machines, and 
I doubt that unrestricted "phonetic typewriters" are a 
part of the next decade or more of practical work on 
speech recognition [Ref 10] . 


2. 

Value of Speech 

Recognition System. 

5 



Speech input 

to machines can be of signif 

icant 

value, 

but under what conditions or 

situations? 

This 

section 

discusses 

some of the 

advantages 

and 

disadvantages of speech 

input described by 

Dr. Lea. 



32 



Speech systems offer the potential to capitalize 
on the best of man's communicative abilities, give him 
compatibility with unusual circumstances, and help him gain 
additional mobility and freedom in some situations [Ref. 
ll]. Speech is said to be the human's most natural 
communication miodality. It is familiar, convenient, and can 
be used spontaneously because the individual uses it often 
in all types of situations. Though performance with voice 
may degrade under situations of stress, it may not degrade 
as much as a less learned, less frequently used skill. 
Since voice is familiar to the user, it is less difficult to 
train him to use the system. Additionally, voice is the 
human's highest-capacity output channel, and permits 
simultaneous communications with humans and machines. For 
example, a speaker in a large auditorium or a command center 
can display the next visual on a large screen display by 
saying some key phrase or word which has meaning to both 
listener and display system. To illustrate, when Dr. Pocck 
recently briefed a group of senior naval officers in the 
Pacific, he used such key phrases as "Good Morning 
Admiral..." to begin his briefing, and "here you see the 
(pause) SKIPS ..." to convey briefing information and tell 
the command and control graphics display system to present 
the next graphic in his presentation on the subject of Voice 
Input for Command and Control. This is just one 


33 






illustration of the creative ways man can use voice input to 
his advantage. 

Navy feasibility studies sponsored by Naval 
Ilectronics Systems Command, and conducted by Dr. Poock, 
examined the potential for voice data entry fcr commend, 
control, communications, and intelligence. Two voice 
recognition systems were installed in late 1960 at Fleet 
Headquarters, Commander-in-Chief of the Pacific (CINCPAC) in 
Hawaii to examine the benefits and limitations of voice 
input for operation of the Worldwide Military Command and 
Control Time-Sharing System (WWMCCS TSS) and the nearby 
Ocean Surveillance Intelligence Systerr (OSIS). One 
advantage of many of the new voice terminals is that they 
are stand-alone, intelligent terminals with standard 
communications interfaces and character sets that can be 
interfaced rapidly with computers possessing those same 
generic interfaces. Voice units may be moved around easily 
and installed as simply as most ether modern RS-232 plug- 
compatible terminals. Voice may also be used remotely as 
much as 2000 feet from the main computer, free from any 
panel space, displays, or complex apparatus. 

The advantages of voice input fcr 
complementing the communicative abilities of man are 
offset somewhat today since a user cannot speak totally 
naturally, but must insert pauses in between utterances, and 
must use utterances within the constraints of the voice 


34 



system's stored vocabulary. This requires the user to 
be very familiar with the vocabulary in use, not 
unlike knowing the letters of the alphabet. 

Speech input for machines is also of value in 
helloing man cope with unusual circumstances. For example, 
it can be used in complete darkness, around obstacles, by 
the blind and other handicapped individuals, is unaffected 
by weightlessness, and only slightly affected by high 
acceleration and mechanical constraints. On the negative 
side, it is often sensitive to dialect, and also susceptible 
to background noise and distortions. Additionally, a 
microphone must either be worn or held in close proximity to 
the speaker. And finally, a display or synthesized voice 
feedback may be necessary for tasks requiring data entry 
validation. 

The mobility possible with voice input is one of its 
greatest attributes. It enables operation of devices from a 
distance and from various orientations, permits simultaneous 
use of hands and eyes for other tasks, and can even permit 
the telephone to be used as a computer terminal. Some 
degree of privacy is lost, although users often operate in 
the laboratory at NFS inconspicuously running graphics 
displays and other command and control applications without 
bothering other nearby terminal operators. 

The key questions to keep in mind when considering 
the value of speech input are: "is there an application that 


35 




I 


coiald be done more cost-effectively using vcice as a single 
or additional input modelity?...and, " Is the current 
technology adequate to provide the quality, naturalness, and 
speed that the application of interest requires?" A brief 
loch at the military's efforts in voice technology may help 
the reader to further assess the value of speech technology 
for his own application. 

3. Military Researcn and Applications 

Research supported by the Advanced Research Projects 
Agency (DARFA), which funds leading-edge technology, was a 
prime ingredient contributing to the development of voice 
technclcgy. However, a large number of military projects, 
such as the ARPA Speech Understanding Research, met with 
limited success as a great deal of work in acoustic- 
phonetics, speech perception, linguistics, and 
psychcaccustic equipment is still necessary to provide the 
foundation for ASR to approach human performance [Ref 12]. 

Most of the research in the military has turned to 
taking off-the-shelf isolated-word recognizers and adapting 
them to particular applications. Recognition studies in the 
military have been done for applications in aircraft 
cockpits, tactical field data entry, military training 
systems, cartography, command and control of networks, 
wargames and graphics, keyword spotting of communications 
channels, emergency action message composition, and imagery 
interpretation tasks such as mensuration and reporting. The 

36 








applications most clcsel/ related to this thesis are the 
cartography, command and control of displays, and imagery 
interpretation reporting. 

A significant amount of research was performed for 
the Defense flapping Agency(D^'A) by contractors under the 
program management of the Air force's Rome Air Development 
Center(RADC ). The Defense flapping Agency Aerospace Center 
(DMAAC) and the Defense Mapping Agency Aerospace and 
Hydrographic Center (DMAHC) produce large volumes of 
cartographic products for the military and other users. 
Research has been performed for such applications as voice 
data entry for the processing of Digital Landmass System 
(DIMS) data, preparation of Ilight Information Publications 
(FLIPS) data, and ocean-depth neasurements for digitized 
cartographic applications. In these applications analysts 
were performing tasks in an "eyes busy, hands busy 
environment," sometimes with stereo optics and or other 
special devices. Voice was shown experimentally to be 
faster, easier, and a less fatiguing mode of data entry than 
the more conventional modes used [Refs. 13, 14, and 13]. 
User acceptance and system support can be significant 
problems, as explained by DMAAC officials to the author 
during a recent visit to their facilities. 

The NPS is currently performing voice data entry 
research in the area of command and control applications. 
In a study by Pocck, twenty-four command and control 


37 



students operated the AEPA network or AP.PANIT, a distributed 
network of computers in the U.S. and Purope, using voice and 
typing as a comparison between the two modes [Ref. 16]. 
Voice was significantly faster and more accurate for 
entering commands into the system. Additionally, students 
were given an secondary transcription task to perform while 
operating the ARPANET. The voice mode permitted 
substantially more data to be transcribed than the typing 
mode. On the other hand, McSorley recently demonstrated 
that voice was no faster than typing for entering commands 
into a vargame. This was due in part to the poor editing 
features of the game, but demonstrates that voice is not for 
everything [Ref. 17] . 

In the area of imagery interpretation, interest in 
voice data entry is growing. RADC recently completed a 
study which evaluated a voice recognition system known as 
"Talk and Type," built by Threshold Technology Inc., to 
study the application of voice data entry to the problem of 
imagery interpretation and intelligence report generation 
[Ref. 18], The innovation by Threshold required the user to 
type the first letter of the word to be recognized. In this 
manner the voice system restricted the size of the 
vocabulary to be searched, thereby increasing recognition 
accuracy. Four varied tests were performed looking at small 
and large vocabularies, and especially tasks where the 
subject was describing scenes the way an interpreter might 


38 


describe a bridp^e or a runway. The results showed the Talk 
and Type system to be superior over typiUis: for unskilled 
typis t s. 

Soon the new ground station for the Tactical 
Reconnaissance-1 iTR-1) aircraft is expected to be built to 
provide exploitation and reporting support for the sensors 
aboard the U-2 derivative aircraft which is expected to 
provide NRT reconnaissance support tc theater forces. 
According to the program manager, voice data entry is a 
serious consideration for inclusion into the program. 

D. SUI^MARY 

The purpose of this thesis is to investigate the 
potential application of ASR technology to military imagery 
interpretation. The research responds to the need for 
rapid, concise, valid information for command and control 
of forces in peace and war. The functions of the imagery 
reporting systems include support for a variety of 
tasks, especially composing reports. The specific focus 
cf the thesis is to examine the feasibility of 
writing order of battle reports using a large voice 
vocabulary of 255 words of USSR/Warsaw Pact military 
equipment names, editing commands, and alphanumerics. 

Several examples cf modern operational and 
developmental imagery exploitation and reporting systems 
were briefly discussed which represent potential systems 


39 





4 


■m 


for applioation of voice technology. Incorporation of ASH 
technology could resnlt in improved capabilities in terms 
of speed, accuracy, and completeness of imagery 
reporting. ASR technology makes optimal use of the fact 
that speech is man's most natural input modality, 
while the limited speeds of interpreters typing may not 
optimize advanced reporting system capabilities. 

The advantages and disadvantages of speech were 
presented. Some of the value of speech input awaits 
technological breakthroughs and may not be realized in this 


decade. 

The 

military 

is 

not 

waiting 

however, 

and seems 

unwilling 

to 

pay for 

ail 

the 

has ic 

research 

to push 


continuous speech systems. Instead, the military is hard at 
work with applications efforts with limited-vocabulary, 
isolated-word, speaker-dependent voice recognition systems, 
proven to be reliable and accurate for the right 
applications, while monitoring and sometimes supporting work 
by private contractors, hopefully leading to practical 
continuous speech systems. 

The objective of this thesis is to support military 
applications research efforts aimed at comparing input 
modalities, and afford the intelligence community an 
independent data point regarding the overall evaluation 
of ASR. This research began independent of the related 
RADC research, and thus serves to underscore the 
appropriateness of voice data entry support to the task. 


40 













II. 


LESCRIPTIOK OE THE EXPERIMENT 


A. OBJECTIVES ANE CONSTRAINTS 

The objective of this experiment was to determine if 
state-of-the-art voice data entry equipment wes feasible for 
reporting imagery-aerived order of battle (03) intelligence 
using an interactive computer system. The experiment was 
designed to determine if there wes any significant 
difference in speed, accuracy, efficiency, and subject 
attitudes regarding manual keyboard and voice data entry for 
this task. A large unclassified vocabulary cf 255 words 
containing alphanumerics, commands, and representative 
USSR/Varsaw Pact equipment names was selected for the 
reporting scenario (see Appendix A). Based on recent 
research, voice data entry was expected to be faster, more 
accurate, and preferred by subjects over manual keyboard 
data entry [Ref. 18]. 

Accomplishment of this objective was constrained within 
the research facilities of the Naval Postgraduate School 
(NPS). In the interest cf time and money, the process of 
reporting was simulated to the maximum degree possible 
within the constraints of available subjects and laboratory 
facilities. This simulation, though not ideal, afforded an 
effective, economical tool to accomplish this objective. 


41 



B. SUBJECTS 

Twenty subjects participated cn a vclunteer basis. 
The group was composed of 13 military officers, and 
two civilians. The military officers, representing the 
Army, Navy, Air Force, and Marines included 17 males and 1 
female; tneir grades ranged from Lieutenant to Commander 
and from Captain to Lieutenant Colonel, The civilians 
included an employee of the National Security Agency and 
a professor from the NFS Operations Research Department. 
The subjects' ages ranged from 28 to 45, with an average age 
of 33. 

Seventeen of the subjects were enrolled in the Command, 
Control, and Communications (C3) Curricula at NFS, while the 
other two students were from the Intelligence and Computer 
Science curriculas. The background of the subjects were 
quite varied: special warfare; ground combat; communications 
maintenance and staff; logistics staff; automatic data 
processing; training; intelligence; C3 research; language 
analysis; electronic warfare; Joint Chiefs of Staff; field 
artillery; destroyer group staff; combat development; C3 
training and operations; and tactical C3 flight operations. 

Nineteen of the subjects had experience with interactive 
computer systems at NFS. Eighteen of the subjects were 
experienced in use of the ARFANZT, a network of computer 
systems available for use by the C3 Curricula and other 
researchers at NFS. The two subjects without ARPANET 


42 


I 


i 

4 

i 


experience were trained to tne level necessary to 
participate in the experiment with their contemporaries, 
since a computer on the ARPANET was chosen as tne host for 
the experiment. 

The subjects were, as a whole, familiar with speech 
reccgnition as many had either seen, used, or even studied 
automatic speech recognition. Eighteen subjects had seen a 
voice recognition system demonstrated? 12 subjects had used 
voice, primarily as subjects in one other experiment? and 11 
had studied voice for a term paper, thesis, or work at their 
previous duty station. 

C. EQUIPMENT 

1. Voice Recognition System 

A Threshold Technology Inc. Model T602 voice 
reccgnition system was used to represent commercially 
available, state-of-the-art equipm.ent. The T600 is a 
speaker-dependent, isolated-word recognizer which 
automatically recognizes spoken words or phrases. These 
words or phrases are called utterances and must be in a 
range of 0.1-2.0 seconds in duration and must be separated 
by very short pauses of 0.1 second or more [Ref. 19]. 

The terminal consists of a threshold analog speech 
preprccesscr, an LSI-11 microcomputer and a digital RS-232 
input/output interface, an Ann Arbor large character 
display and operator console, an operator console/microphcne 


43 









preamplifier, and a tape cartridfe^e unit. The speech 
preprocessor, microcomputer, and interfacing elements are 
contained in the main terminal unit which was table mounted. 
The remaining components, the display console, and tape were 
disc table mounted and located with the main terminal (see 
Figure 7). A Shure SN-10 noise-cancelling microphone with 
headset was used for the voice input to the preamplifier. 

The T600 combines analog and digital signal 
processing technology to perform the recognition function. 
The energy from the spoken utterance is passed through 19 
bandpass filters spanning the speech spectrum. The presence 
or absence of each of 32 acoustic features is determined, 
and the appropriate feature information is extracted by a 
combination of analog and binary logic. The features are 
either primary features or phonetic-event features. Primary 
features describe the energy spectrum by measuring local 
maxima and the energy rate-of-change relative to the 
frequency of the voice signal. Phonetic-event features 


result 

from measurements 

corresponding 

to 

phoneme-1 ike 

events: 

vowels, nasals and 

fricatives. 

The 

preprocessor 


also must determine the beginning and ending of each word. 


44 



, It St. old 'i 11 iiriol Of- 










The T600 has two primary nodes of operation: 
training mode, and recognition mode. In the training mode, 
the 1600 extracts a time-normalized template for each given 
word. Ihis template consists of two arrays referred to as 
the most significant tit (hSB) and non extremum tit (NEB). 
The h'SB indicates whether a particular feature has occurred 
and the NEB indicates the frequency of occurrence. These 
arrays combine to form the reference array (HAR) . When the 
T600 is in recognition mode, the preprocessor functions as 
before: features are extracted, digitized, and time 
normalized. The resultant feature array (JAR) is correlated 
with the stored RARs in the current active vocabulary and 
the best correlation is selected as the recognized word. 

As previously mentioned, for each utterance 32 
acoustic features represented in binary form and their time 
of occurrence are fed from the preprocessor to the 
microcomputer short-term memory. The pattern-matching 
algorithm subsequently compares these feature occurrence 
patterns to the stored reference patterns for the various 
vocabulary words and determine the "best fit" for a wcrd 
decision. The JAR of a test word requires 512 bits of 
information (32 features m.apped into 16 time segments). The 
RARs include 1024 bits per word because of the two part 
arrays. 

When the Te00 recognizes a word in its vocabulary it 
will output a preprogrammed string of up to 16 characters 


46 


associated with the spoken worn. These output strings can 
he modified hy the user at any time via his ASCII console, 
which may also he used instead of voice to interact with the 
host computer. Also associated with each word are training 
prompts which are strings of up to 12 ASCII characters 
displayed on the CP.T terminal to notify the user of the word 
to he trained. The T600 used in this experiment rec^uired 10 
training utterances per word. 

Two types of errors can occur with the Te00: 
misrecognition and rejection. Misrecognition errors are 
those where an output string is selected for output that 
does not match the utterance. When the system rejects the 
utterance as not part of the vocabulary it signals the 
operator with a "heep." These two cases assume the word was 
in the vocabulary and properly trained. Other errors are 
called operator errors and arise from mispronunciation, 
using words not in the vocabulary, or a variety of other 
errors such as speaking too fast or slow. 

The T600 used had enough memory modules to maintain 
an active working vocabulary of 256 utterances. 
Vocabularies were input and output using the tape cartridge 
unit. The system reads and stores prompt and output strings 
and reference patterns from semiconductor random access 
memory onto rugged, high-quality magnetic tapes similar to 
cassette tape cartridges. A complete 256 word vocabulary 
may be recorded or loaded in a few minutes. 


47 


Two recognition modes are available on the 1622 : 
unbuffered and buffered. In unbuffered mode, the T600 will 
send any output immediately to the host computer. No 
internal processing is performed on the output strings. 
However, the buffered mode permits up to 126 utterance 
output strings to be sequentially stored in a T 600 buffer 
for subsequent output as a composite block of characters. 
An "erase function" may be used to delete the last 
utterance; an "interrupt" function sends a special user- 
defined string to the host and deletes the remainder of the 
buffer contents; a "cancel" function may be used to delete 
the buffer contents; and a "transmit" function will cause 
the T600 to send the buffer contents to the host. The 
utterance assigned to these functions may be independent of 
their function name. 

2. Tachistoscope 

To provide a simulation of the light table 
and optics portion of the imagery interpreter's work 
environment, the G-1130 Harvard Tachistoscope was 

selected from the man-machine laboratory facilities, 
(see Figure 6) The tachistoscope is an instrument that 
can present images of material presented on cards and, 
as modified in this experiment, a CRT display. The card 
images may be presented by a timer or changed at will by the 
subject using a button switch. Lighting may be regulated 


46 




49 


'ure b. ’lacaisioscopfe liiierfaced lo hnn Arbcr LhT Disilay chu 

















end rriult i-ims^es overlayed. The three primary uses of the 
device are studies on learning, perception, and attention 
[Ref. 20] . 

However, in this experiPient the tachi stoscope was 
used in the following manner. The viewport seen in Figure 9 
simulates the optics through which an interpreter must get 
much of his/her data. The 4" x 6” cards seen through it 
simiulated the imagery the interpreter was tasked to analyze 
and report. The CRT presented three lines of data (40 
characters each) providing visual feedback for voice data 
entry. (Note; Rome Air Cevelcpment Center has developed an 
eyepiece for a Bausch & Lomb stereoscope that displays 16 
characters of data while viewing the optics) thus the author 
assumed that more data could be displayed in the next few 
years to support such visual feedback, if required.) 

The tachistoscope viewport permitted the viewing of 
the scenario cards and the Ann Arbor CRT. The card image 
was centered above the three bottom lines of the large- 
character CRT. The CRT displayed the responses of the Te00 
to the subject's utterances, thereby providing visual 
feedback to him/her performing the task. 


50 






















1 


Figure 9. Tachistoscope Viewport 












Scenario Cards and Vocdbulary 


The cards for the reporting scenario were used to 
simulate frares of irrager/. Because no imagery interpreters 
were available in large numbers for the experiment at NFS, 
the author created the cards with a to represent the 
equipment location and annotated the with the number 
and description of the equipment at the point. All subjects 
were provided with the same information, i.e. they were 
"perfect imagery interpreters" and any experience level was 
held constant. 

Figure 10 illustrates the format of two sample cards 
which had five to eight objects and an installation number, 
lach card was divided into four quadrants to simplify and 
standardize the reporting process and scoring. 

Thirty-six cards were required for the experiment. 
Their content was governed by four criteria: realism, an 
even mix of ground, air, and naval terms, full use of the 
USSP./Warsaw Fact vocabulary selected for the experiment, and 
maintaining a balance in number of characters among sets of 
cards to be used in experimental trials. The cards used in 
the experiment are shown in reduced size in Appendix 3. The 
larger, actual size cards seen in Figure 10 were produced 
using large print on a Tektronix 4014 terminal and its 
associated thermal printer. 


52 









INSTALLATION e298-T14217 


50 CONFIRPIED ASU-85 

27 CONFIRHED ASU-57 
tt 


tt 


AIRBORNE ASSAULT GUNS 
AIRBORNE ASSAULT GUNS 


tt 20 POSSIBLE n-20 
62 PROBABLE 122-nn D 

48 CONFIRNED 240-nn 

tt 


HEAUY nORTARS 
30 FIELD HOUITZERS tt 

Bn-24 ROCKET LAUNCHERS 


INSTALLATION 0199-U14197 

16 CONFIRNED ni-4_H0UND HELICOPTERS 


tt 


tt 

11 CONFIRNED ni-12_ 
tt 5 PROBABLE ni-6J 


HOnER HELICOPTERS 

I 

HOOK HELICOPTERS 


21 CONFIRNED ni-10_HARKE HELICOPTERS 


19 PROBABLE ni-24_HIND HELICOPTERS 


7 ^' r r p 1 

i-c. 

(actLdl size 


crple Seer.eric ‘'avis 


= ^ 


A O 


includinsT 'oordsr'' 






































A USSR/Wersaw Pact vocabulary was used because of 
available unclassified source inforration in large quantity 
[Refs, cl, 22, 23,and 24]. A full vocabulary cf 255 words 
was used containing the phonetic alphabet, nurnbers 2-25, 
administrative aIphanumerics, special symbols and control 
characters, and ground, air, and naval forces equipment 
vocabulary. Appendix A contains a complete listing of the 
vocabulary by number, training prompt, and output string. 

The vocabulary was not structured in term.s of 
recognition sets. Rather, the T620 operated on the entire 
vocabulary each time an utterance was spoken. 

4. Interactive Computer System: ARPANZT 

To provide an interactive text editing environment 
for the reporting scenario, the facilities of the ARPANET 
were selected because of their reliability and also to 
demonstrate how reporting niight be done over a distributed 
network of computers, rather than a local host system. The 
ARPANET, now managed by the Defense Communications Agency, 
was used by 18 cf the subjects during 5 quarters of their C3 
Curricula prior to the experiment. 

Two host computers were used: Information Sciences 
Institute Systems E and C (ISIE 6. ISIC), located in southern 
California. The experimental text editor (XED), photoscript 
(PHOTO), directory linking (TALK), file transfer protocol 
(ETP), and file archival (ARCHIVE) were the major programs 


54 



used to conduct and manage the experimental data end 
interactive computer environment. ISIC was the primary 
system used, because the "system load level" was generally 
lower thereby offering a more responsive system. The load 
level was checked during experimentation to assure a 
consistent response time was available to all subjects. 
Both systems were supported by the TOPS-cZ Operating System, 
on Digital Equipment Corporation (DEC) Model 20 Computers. 

These computers were linked to NFS terminals 
equipped with phone moders or acoustic couplers via 
the ARPANET distributed communications facilities. 
These facilities include a terminal interface processor 
(TIP) at NPS connecting school terminals with ISI via 
the ARPANET. The author gained access to the network 
via the TIP and selecting the network computer to be 
used. The ARPANET providea a myriad of facilities 
supporting the administration of the experiment. Figure 11 
is a map of the ARPANET adapted from, the ARPANET Information 
Brochure, 1979. 

CRT terminals and the T600 were attached to the 
ARPANET via 30£ bps acoustic couplers. A lier-Siegler 
ADM CRT display was situated near the tachistoscope to 
provide keyboard entry of the OB data obtained from the 
cards via the viewport (see Figure 12). The ADM terminal on 


53 
















^Lectmber, 19Vf 







c7 


Aita(iied tc ISI Ccnipiiter via the ARPANET 









the ARPANET was used to sirr.ulate the text editing facilities 
cf an imagery reporting system for the order of tattle entry 
portion of the report. All keystroke entries into the 
terminal were copied ty a typescript program, during the 
experiment to provide a record of the subject's performance. 

A monitor station with a hardcopy Computer Devices 
Miniterm and an Alanthus V-203 CRT display were used to 
record and observe the subject's actions, whether by voice 
or keyboard entry (see Figure 13). The Alanthus display, 
connected to the 1602, provided the author with a copy cf 
the data being displayed to the operator via the Ann Arbor 
display used in the tachistoscope viewport for visual 
feedback. This was essential for recording, recognition and 
rejection errors in the voice-buffered mode; such errors 
could not be analyzed from the hardcopy record if edited 
from the voice buffer prior to transmiission of the buffer 
contents to the text editor. 

D. SUBJECT PREPARATION 

1. T600 Vocabulary Training 

Prior to the experiment, subjects were individually 
trained in the use of the T6e0 to a level of knowledge and 
competence to allow them to operate it to train the large 
vocabulary of 255 words. Each subject was briefed on the 




59 


r ini tern haracop,/ ternincl 









proper training of the TtZd, and received a derronstrat icn 
and written instructions with the training (see Appendix C). 
Cnee the subject had deironstrated proficiency in operating 
and training the 1600, he/she was allowed tc proceed 
independently, with the author remaining nearby to answer 
questions and correct training pitfalls. Once training was 
complete, the subject tested the vocabulary by saying each 
word three times. Any words which were misrecognized or 
rejected more than once were retrained until a goed training 
pattern was established. Most retraining was required 
because the subject forgot how the word was pronounced when 
initially trained. 

The training was normally accomplished in two 
sessions of approximately two hours each. Thus by the time 
the training was complete, the subject was very familiar 
with the Te00. Approximately four hours was the average 
time each subject spent with the vocabulary prior to 
experimentation. The training patterns were stored on a 
cassette tape for each subject and retained by the author 
until experimentation. 

2 . Typing Test 

A five minute typing test was given to each subject 
to group the subjects into 'FAST" and "SLO" typing ability 
groups; these groups were necessary for the experimental 
design. The typing test required only upper case letters 
and symbols (Appendix D), as did tne experiment. 


60 
































The typine' test was administered and scored 
similarly to the civil service test used to screen clerk- 
typist applicants to determine their typing- ability. 
The typing tests were scored for speed and accuracy. A 
raw score in words per minute was assigned according to 
the number of lines typed. Credit was given for all lines 
typed, including any portion of the last line started. 
The number of words per minute was based on an average word 
length of five characters. For each mispelled word, 0.2 
words per minute were subtracted from the raw score, 
tnereby decreasing the final score to deduct for errors. For 
eianple, if a subject had a raw score of 40 wpm, but made 5 
typing errors, the final score would be 39 wpm. 

Subject typing speeds ranged uniform.ly from 17 to 
58 words per minute, with an average speed of 43 words per 
minute. The SLOW typist scores ranged from 17 to 32 
with an average of 25? FAST typists scores ranged from 33 to 
53 with an average of 43. 

3. Subjective Questionnaire and Data Sheet 

To assess the attitudes of each subject before and 
after experimentation regarding their assessment of voice 
data entry versus typed data entry, a 10 item subjective 
•luestionnaire was developed (see Appendix I). The 
questionnaire asked for the subject's opinions regarding the 


61 




voice and typing modes on concerns relating to usability 
such as speed, accuracy, flexibility, training, and other 
criteria. 

Subjects also completed a short data sheet regarding 
age, previous job, background, next assignment, and voice 
experience. Appendix I contains the data sheet format. 

E. EXPERIMENTAL PROCEDURE 

As soon as the subject completed the vocabulary 
training, he/she was scheduled to perform the experiment 
which lasted between two and four hours, depending on the 
speed of the subject. The experiments were conducted in the 
iNPS Man-Machine Lab at times most convenient to the subject, 
generally in the evening. 

The subject was briefed concerning the general purpose 
for the experiment and the three major parts of the 
experiment: typing mode, voice-unbuffered mode, and voice- 
buffered mode experimental conditions (see Appendix G). 
Each experimental condition consisted of a practice card and 
three trials. A Latin-Square determined the order of the 
experimental conditions such that a balance was maintained 
in the numbers of people starting each experimental mode. 
This balance was also maintained on the second and third 
experimental conditions for the subjects. In other words, 
care was taken that no experimental condition received an 


62 

































advantage froni always being first, second, or third- 
Subjects were assigned randomly tc the orderings. 

The subject's task for each aata entry mode was to write 
12 simplistic on-line imagery interpretation reports of the 
USSR/Warsaw Pact OB obtained from the cards by looking 
through the viewport of the tachistoscope. Four cards were 
included per trial for the three trials per mode. 

Recall the sample cards in Figure lo; they were used for 
typing (top) and voice (bottom) modes respectively, and 
differed slightly. Since some utterances were actually two 
or three words, (e.g. MIG-25 F0X3AT) and since the 
vocabulary of equipment names were so large, it was 
unrealistic to eipect the subject to recall which ones were 
multiple words without greater familiarity with the 
vocabulary. A convention was adopted to link such words 
with an underscore symbol (_), such as MIG-25_F0XBAT, to 
remind the subject that the name was tc be said in a single 
utterance vice two or three utterances. The underscore was 
the only distinction between the cards for voice and typing 
modes. 

The report format is shown in Figure 14. The subject 
was required to report the installation number and C3 
location (**) by quadrant in the order shown: UPPFR LEFT, 
UPPER RIGHT, LOWER LEFT, LOWER RIGHT. Reports were to be 
separated by a blank line. 


63 





I 


4 


INSTALLATION 0298-114217 
UPPER LEFT 

27 CONFIRMED ASU-57 AIRBORNE ASSAULT GUNS 
UPPER RIGHT 

£0 CONFIRMED ASU-85 AIRBORNE ASSAULT GUNS 
LOWER LEFT 

20 POSSIBLE M-20 HEAVY MORTARS 

48 CONFIRMED 240-MM BM-24 ROCKET LAUNCHERS 
LOWER RIGHT 

62 PROBABLE 122-MM D-30 FIELD HOWITZERS 

INSTALLATION 0199-V14197 
UPPER LEFT 

11 CONFIRMED MI-12 HOMER HELICOPTERS 
6 PROBABLE MI-6 HOOK HELICOPTERS 
UPPER RIGHT 

16 CONFIRMED MI-4 HOUND HELICOPTERS 
LOWER LEFT 

19 PROBABLE MI-24 HIND HELICOPTERS 
LOWER RIGHT 

21 CONFIRMED MI-10 HARKE HELICOPTERS 

Figure 14. OB Reporting Format Based on Cards in Figure 10 


64 




























Subjects were allowed short breaks between trials and 
longer breaks between the entry modes as they moved for 
exapple from the typing portion to the voice-unbuffered 
portion or vice-versa. 

The number of characters per trial was balanced to a 
very high degree within 10-lb characters and 10-15 
utterances for all modes. The average number of keystrokes 
per trial for the typing mode was 1170. The average number 
of utterances per trial for the voice-unbuffered mode was 
220/trial, slightly less than the 22e/trial for voice- 
buffered. These keystrokes and utterances did not count any 
editing keystrokes or utterances, but included all carriage 
returns required. To perform the 3 modes i 3 trials, a 
minimum of approximately 3510 keystrokes and 1344 utterances 
would be required, plus any editing. 

Prior to beginning each experimental condition the 
subject was briefed on the entry mode, reminded of the 
editing features available (delete character, delete word, 
delete line, and repeat line), and allowed to practice the 
entry mode by writing a report for a practice card. 

The experimenter monitored the entire experiment at the 
station illustrated in Figure 13. The elapsed time to 
complete each trial was measured using a digital stopwatch 
and recorded. The Miniterm provided a typescript for 
analysis of the reports for missing or extra Information, 
resulting from typing or voice recognition errors. Fxtra 


65 



I 

4 


I 




I 


I 


■'i;? 



typing -ceystrokes or voice utterances used for editing out 
errors were noted for subsequent analysis for an efficiency 
reasurement. The CRT display was used for the unbuffered 
voice mode to record the misrecognitions and rejects since 
they did not appear on the typescript if they were edited 
prior to buffer transmission. 

At the conclusion of the experiment the subject 
completed the subjective questionnaire again. The subject 
was asked not to discuss the experiment with others. 


F. DEPENDENT VARIABLES 

The following variables were recorded or calculated in 
per cent for each trial: 

NCC 

Report Accuracy (RA)= - X 100 

NCC + OS + CE 

where NCC: Number of Characters Correct 

OE: Omission Errors/missing data 

CE: Commission Srrors/extra data 


NCE/U 

Mode Efficiency (MS) = -X 120 

NCE/U + EK/U + SDK/U 

where NCI/U: Number of Correct 

Keystrokes/Utterances (Typing/Vcice) 
SK/U: Error Keystrokes/Utterances 

EDK/U: Editing Keystrokes/ Utterances 
used to recover errors 


66 








NCR 

Reccgniiicn Accuracy (RA) = -X ICC 

NCR + NM 

where NCR: Number of Correct Recognitions 

NM; Number of Misreccgnitions 

NCR 

Recognition Accuracy (RAR) = - X 100 

with Rejects NCR + NM + NR 

where NCR: Number of Correct Recognitions 

NM: Number of Misrecognitions 
NR: Number of Rejects 

Perhaps the most imiportant variable was the time it took 
for a subject to complete the trials in the experiment. 
Close behind time is accuracy, since reports must be valid 
in addition to timely. Thus it is important to look at 
report output in terms of accuracy as a system product. 
Frequently experimenters examine the errors made with voice 
and typing and report the results as percentage of error. 
However in this experiment the final test is in the report 
produced ... is it accurate? Next, how efficient is the 
data entry mode? This is also a useful statistic for 
judging the merits of each system. Accuracy and efficiency 
were basic measures of the total system capability, l.e. the 
man and the machine. Recognition accuracy was a measure of 
TS00 performance alone, with operator errors such as 
mispronunciation removed. Two recognition accuracy measures 
were examined, but the first is considered most appropriate 
in this experiment since the T60e did not output Incorrect 


67 





















data but beeped when it rejected what should have been a 
valid vocabulary utterance. 

G. HYPOTHESIS 

The following hypotheses were tested: 

1. Hypotheses Regarding Tib’S 


a. Eo : 

There is no difference in TIME to 

complete reports between FAST 

and SLOW typists. 

H, : 

Eo false. 

b. Ho : 

There is no difference in TIME to 

complete reports among the 

THBEE DATA ENTRY MODES. 

E, : 

Eo false. 

c. Ho : 

There is no difference in TIME to 

complete reports among the 

THREE TRIALS. 

H/ : 

Ho false. 


2. Hypotheses Regarding ACCURACY 


a. Ho : 

There is no differenoe in ACCURACY of 

reports between FAST and SLOW typists. 

H, : 

Ho false. 

b. Ho : 

There is no difference in ACCURACY of 

reports among the THREE DATA ENTRY MODES. 

K/ : 

Ho false. 


68 




I 




i 


I 







c. Ho : There is no difference in ACCURACY cf 
reports among the THREE TRIALS. 

Ej : Ho false. 

Hyootheses Reeiardins EFFICIENCY 


a. H/ 


h. 


H/ 

K, 


There is no difference in EFFICIENCY 
between FAST and SLOW typists. 

Ho false. 

There is no difference in EFFICIENCY 
among the THREE DATA ENTRY MODES. 

Ho false. 

There is no difference in EFFICIENCY 
among the THREE TRIALS. 

Ho false. 


4. Hypotheses Regarding T60e RECOGNITION ACCURACY 

WITHOUT REJECTS 


a. 


b. 


Ko 

K/ 

Eo 


There is no difference in RECOGNITION 
ACCURACY between FAST and SLOW typists 
Ho false. 

There is no difference in RECOGNITION 
ACCURACY among the TWO VOICE MODES. 

Ho false. 

There is no difference in RECOGNITION 
ACCURACY among the THREE TRIALS. 

Ho false. 


69 


















Hypotheses Regaraing T600 RECOGNITION ACCURACY 
WITH REJECTS 


6 . 


a. 


Ho 



c . 


H/ 

Ho 


H/ 

Hypothe 


: There is no difference in RECOGNITION 

ACCURACY WITH REJECTS between FAST and 
SLOW typists. 

: Ho false. 

: There is no difference in RECOGNITION 

ACCURACY WITH REJECTS amonfir the TWO 
VOICE MODES. 

: Ho false. 

: There is no difference in RECOGNITION 

ACCURACY WITH REJECTS arr.ong the THREE 
TRIALS . 

: Ho false. 

sis Regarding SUBJECT ATTITUDES 


Ho : There is no difference in SUBJECT 

ATTITUDES regarding a preference for 
VOICE DATA ENTRY over TYPED DATA 
ENTRY after the experiment. 

K/ ; Ho false. 


H. EXPERIMENTAL DESIGN 

The conceptual design for the experiment is illustrated 
in Figure 15. This is a three-factor nested design with 
repeated measures over trials. The subject is nested within 
only one typing ability condition. Recall that one-third of 


70 





FAST 


TYPING 

ABILITY 

(TA) 


SLOW 



TYPING V0IC3 VOICE 

UNEUFEIRED BUFFERED 

DATA ENTRY MODE (DEM) 


Figure 15. Conceptual Design of the Experiment 


71 












the subjects started typing first; another third started 
voice-unbuffered first, and another third started 
voice-buffered first. 

An analysis of variance procedure was selected to test 
the hypotheses for reporting times, accuracy, and 
efficiency, and T60? recognition rates. A significance 
level of oc = 0.0c was used as the experimental threshold. A 
sign test was chosen to evaluate the subjective 
Questionnaire results at a significance level ofac= 0.10. 

I. RESULTS 

1. Results for Reporting Time 

The results for reporting time were the most 
significant, with an analysis of variance (ANOVA) indicating 
SIGNIFICANT DIFFIRINCFS in the DATA ENTRY f^ODES and TRIALS 
^p < .0005). The mean reporting times in Table I show the 
average time in minutes to complete each of the reporting 
trials for each of the three data entry modes. Table II 
displays the results of the ANOVA for reporting time, and 
Figures 16 and 17 illustrate the significant differences. 

On the average, voice-unbuffered was 41% faster and 
voice-buffered was 56% faster than typed data entry. Thus 
voice data entry, averaging the two modes, was 50% faster 
overall than typing. Voice data entry was faster because the 


7Z 










subject was able tc simultaneously receive information 
through the viewport while composing the report. The 
feedback received on the monitor enabled immediate 
confirmation of the T6i30 response to his/her utterances. 
The typist, in the conventional reporting mode, was forced 
to return often to the viewport to get additional items of 
information, since there was too much to memorize. The 
illustrated differences may be seen in Figure 16. 

Learning over trials is apparent in all three data 
entry modes. Figure 17 illustrates the differences in time 
to complete the scenario by trials. No significant 
differences were noted between typing abilities. All 
subjects adapted to the reporting task well. The voice- 
buffered mode was the most natural for subjects to use, 
since they could simply speak the report into the system, 
and make corrections most easily. Thus they learned to use 
it quickly, and improved slightly thereafter. The voice- 
unbuffered and typing modes, with more room for improvement, 
showed more learning as the subjects adapted to the 
reporting scenario. 

No significant difference was apparent between fast 
and slow typists for this eiperinent. This was primarily 
because the amount of information that the subject could get 
from the tachisto scope was limited to the amount he/she 
could memorize when moving back and forth to the manual 
keyboard. 


73 


I 


J 

I 

4 



ABLE I 


MEAN REPORTING TIME (MINUTES) 




TYPING 

VOICE 

UNBUFFERED 

VOICE 

BUFFERED 

FAST TYPISTS 

Trial 1 


16.2 

11.6 

10.5 

Trial 2 


13.6 

10.5 

10 .1 

Trial 3 


13.2 

9.6 

9.1 

All Trials 


14.3 

10.6 

9.9 

SLOW TYPISTS 

Trial 1 


16 .0 

12.7 

10.0 

Trial 2 


16.6 

10.6 

9.8 

Trial 3 


15.6 

10.5 

9.2 

All Trials 


16.7 

11.3 

9.7 

ALL SUBJECTS 

Trial 1 


17.1 

12.2 

10 .3 

Trial 2 


16.1 

10.7 

10.0 

Trial 3 


14.4 

10.1 

9.2 

All Trials 


15.6 

11.0 

9 .8 

For 

the 

foil owing 

analysis of 

variance several 

abbeviations 

are 

used for 

the sake of 

brevity. Their 


ireauing is expanded below: 


SS: Sum of Squares 
df: degrees of freedom 
MS; Mean Square 
F: F Ratio 

p: significance level 


74 





.'■fe 



.l-M 





TABLE II 


ANALYSIS CF VARIANCE FCR REPORTING TI^'E (SECONDS) 


SOURCE 

SS 

df 

MS 

F 

P 

BETWEEN SUBJECTS 

: 3,558,£01.60 

19 




Typing Ability 
(TA) 

149,472.05 

1 

149,492.05 

0 .78 

NS 

Error 

3,439,329.61 

18 

191,073.87 



WITHIN SUBJECTS: 

6,588,801.20 

160 




Data Entry 
rede (DEM) 

3,969,141.26 

2 

1 ,964,570.64 

61.61 


TA X DEM 

167,215.63 

2 

93,607.82 

2.91 

NS 

Error(1) 

1,159,579.54 

36 

32,210.54 



Trials (Tr) 

424,688.41 

2 

212,444.21 

33.22 


T A X T r 

2766.70 

2 

1,383.35 

0.22 

NS 

Error(2) 

230,255.50 

36 

6,395.99 



DEM I Tr 

66,396.02 

4 

16,599.01 

2.28 

NS 

TA I DEM X Tr 

17,872.27 

4 

4,468.07 

0.61 

NS 

Error(3} 

525,207 .79 

72 

7,294.55 



TOTAL 

10,172,124.80 

179 





p < 0.0005 

r NS: NOT SIGNIFICANT for p < 0.05 ] 


75 



^■ZAN TIME 
(rrinutes) 


17 + 



9 


TYPING VCICE-UNBUZFZRZD VOICZ-BUFFERZD 

DATA ENTRY MODES (DEM) 

Figure 16. Mean Reporting Time by Data Entry Mode 


76 


















































MEAN TIME 
(minutes ) 


19 + 

I 

I 

I 

I 

f 

IS + 

I 

[TYPING 

I 

I 

17 +MODE 

j 

I 

I 

I 

I 

I 

15 + 

I 




14 


I 

+ 

I 


I 

I 

13 + 

I 


jUNBUPFSRSD 


12 +MODE 



Figure 17. Mean Reporting Tirre iDy Trial 


77 



'i 

'i 


ck 

' i 

i 

' i 

j 

‘ i 

'I 

(1 

n 

i i 
■ » 
■ 1 

, »■ 

M 

■ i 
-> 



2. Results for Reporting Accuracy 


The results for reporting accuracy are shown in 
Tables III and IV. The analysis of variance fcr the 
arcsin-transforired efficiency data revealed NO SIGNIFICANT 
DIFFERENCES in ALL CONDITIONS investigated. The subjects, 
whether fast or slow typists, did near perfect reporting in 
each mode, over all trials. The reporting accuracy was 
expected to be high, but exceeded the author's expectations. 
An average of 99.5% accuracy was achieved for the 
experiment. 

Subjects were told to go as fast as possible, while 
maintaining accurate reporting. I^ost errors were errors cf 
omission, where a letter or worn was missing from a report. 
Sven greater speeds could be expected, especially from 
voice, in situations where m.ore errors could be tolerated. 
But in the case of imagery reporting, accuracy was deemed 
essential, even though operationally reports are normally 
edited before being sent cut to the agencies. 

TAELI III 

MEAN REPORTING ACCURACY (%} 

VOICE VOICE 



TYPING 

UNBUFFERED 

BUFFERED 

FAST TYPISTS 

99.6 

99.6 

99.7 

SLOW TYPISTS 

99.2 

99.4 

99.6 

ALL SUBJECTS 

99.5 

99.5 

99.6 


78 







TABLE IV 


ANALYSIS OF VARIANCE 

FCR ARCSU-TEANSFORriD REPORTING ACCURACY 
Y = 2 ARCS IN [SQRT( ACCURACY %)] 


SOURCE 

SS 

df 

MS 

Y 

P 

BETWEEN SUBJECTS: 

3.786 

19 




Tyt'in^ Ability 
(TA) 

0 .0ii34 

1 

0.004 

0 .02 

NS 

Error 

3.784 

18 

0.210 



WITHIN SUBJECTS: 

24.030 

160 




Bata Entry 

Mode (DEM) 

0.346 

2 

3.173 

1.16 

NS 

TA X DEM 

0.407 

2 

0.204 

1.40 

NS 

Error(1) 

5.262 

36 

0.146 



Trials (Tr) 

0.352 

2 

0.176 

1.18 

NS 

TA I Tr 

0.202 

c 

0.101 

0.68 

NS 

Err or(2 ) 

5.362 

36 

0.149 



DEM X Tr 

0.395 

4 

0.099 

0 .64 

NS 

TA I DEM I Tr 

0.326 

4 

0.082 

0.53 

NS 

Error(3 ) 

11.078 

72 

0.154 



TOTAL 

27.518 

179 




[ NS: NOT SIGNIFICANT for p 
Note: Arcsin transform above normalizes 

< 0.05 ] 
the per 

cent data 

* 


79 




Results for Reporting Efficiency 


The results fcr reporting efficiency are shewn in 
Tables V and VI. The analysis of variance indicated 
SIGNIFICANT DIFFFRZNCSS between the DATA ENTRY MODES. 
Figure 18 shows the differences with typing being the most 
efficient at 95%, voice-buffered next with an efficiency of 
85%, and finally voice-unbuffered with an efficiency of 60%. 

The author attributes the efficiency difference, in 
part, to the level of experience with the mode. The reader 
may recall that the subjects had, in general, extensive 
keyboard experience during five quarters at NFS. In 
comparison with typing, the subjects had very little 
experience with voice. It is expected that if subjects were 
more skilled and efficient in the use of voice data entry, 
the time advantages reported earlier would be even more 
dramatic. Voice-buffered was more efficient than voice- 
unbuffered because the subject could edit out an entire 
incorrect utterance, vice deleting it by voice a word at a 
time in the unbuffered mode. 


80 
















TABLZ V 



f^EAN REPORTING 

TYPING 

EEEICISNCY {%) 

VOICE 

UNBUFFERED 

VOICE 

BUFFERED 

iAST TYPISTS 

Trial 1 

93.6 

77.2 

63.5 

Trial 2 

95.1 

80.5 

85.7 

Trial 3 

93.6 

81.6 

83 .3 

All Trials 

94.2 

79.6 

84.2 

SLOW TYPISTS 

Trial 1 

94.4 

80.0 

66 .3 

Trial 2 

95.8 

64.4 

64.4 

Trial 3 

96.7 

76.9 

68 .4 



_—— 


All Trials 

95.6 

80.4 

86.4 

ALL SUBJECTS 

Trial 1 

94.0 

78.6 

84.9 

Trial 2 

95.4 

62.5 

85.0 

Trial 3 

95.3 

79.3 

65.8 

All Trials 

94.9 

60.1 

65 .2 


ei 




























































TABLE VI 


ANALYSIS OE VARIANCE 

FOR ARCSIN-TRANSFORMED REPORTING EFFICIENCY 
Y = 2 * ARCSIN [SQRT(EFFICISNCY %)] 


SOURCE 

SS 

df 

MS 


P 

BETWEEN SUBJECTS: 

3.059 

19 




Typing Ability 
(TA) 

0.134 

1 

0.134 

0 .82 

NS 

Error 

2.925 

18 

0.163 



WITHIN SUBJECTS: 

15.689 

160 




Data Entry 

Mode (DE^^) 

7.102 

2 

3.551 

44 .95 


TA X DEM 

0.023 

2 

0.011 

0.14 

NS 

Error(1) 

2.660 

36 

0.079 



Trials (Tr) 

0.17 0 

2 

0.085 

3.54 

NS 

TA I Tr 

0 .020 

2 

0.010 

0 .42 

NS 

Srror(2) 

0.860 

36 

0.860 



DIM X Tr 

0.167 

4 

0.042 

1.40 

MS 

TA X DEM X Tr 

0.301 

4 

0.075 

2.50 

NS 

Error(3) 

2.186 

72 

0.030 



TOTAL 

16.748 

179 





** p < 

0.001 





[ NS: NOT SIGNIFICANT fcr p < 0.05 ] 


82 



.rEAN EFFICIENCY 

100 % + 

I 
I 
I 
I 
I 
I 
j 

95 % + 

I 
I 
I 
I 
I 
I 
I 

90% + 

I 
I 
I 
I 
I 
t 
I 

85% + 

I 
I 
I 
I 
I 
I 
I 

80% + 

I 
I 
I 
f 
1 
I 
I 
I 

I w/b ^ 

I 
I 
I 
I 
I 

I 

II I I 

II I I 

^2% _ 

TYPING VOICE-UNBUJFEP.ED VOICE-BUFFERED 

DATA ENTRY MODES (DEM) 

Figure 18. Mean Reporting Efficiency ty Data Entry Mode 



83 









Results for T600 Recognition Accuracy 


4. 

The results fcr the Te00 Recognition Accuracy are 
shown in Tables VII, VIII, IX, and X. Analysis of variance 
cf the results revealed NO SIONIIICAMT DIFFERENCES fcr ALL 
CONDITIONS considered. Thus the T600 recognized all 
subjects equally well during all trials of the experiment. 
The 1600 recognition accuracy was 97.0% overall if an error 
is defined as a misreccgnition only. If rejects are 
included, the recognition accuracy drops to 96.5% as an 
overall average. 

These results are based on an average of 1519 
utterances per subject giving 30,380 utterances for the 
entire experiment using 20 subjects. This number includes 
the utterances required, plus misrecognitions and reject 
utterances, and finally the editing utterances used to 
correct errors. A list of misrecognitions and rejects is 
contained in Appendix n. 

The author had expected the recognition 
accuracy to get worse in later trials from fatigue or 
frustration, since the experiment was two tc four hours in 
length. One procedure that may have helped was to 
allow subjects to, upon their request, retrain troublesome 
words during the course cf the experiment. The time tc 
retrain was counted against the trial time to account for 
realistic retraining that would take place on the job. 


64 



Table vii 

hEAN T622 RECOGNITION ACCURACY (%) 
WITHOUT REJECTS 




VOICE 

UNBUFFERED 

VOICE 

BUFFERED 

FAST 

TYPISTS 

97.0 

97.1 

SLOW 

TYPISTS 

97.0 

96.9 

ALL 

SUBJECTS 

97.0 

97.0 



TABLE 

VIII 



MEAN T600 RECOGNITION ACCURACY 



WITH 

REJECTS 



VOICE 

UNBUFFERED 

VOICE 

BUFFERED 

FAST 

TYPISTS 

95.8 

95.4 

SLOW 

TYPISTS 

95.2 

95.4 

ALL 

SUBJECTS 

95.5 

95.4 


65 






{ 





TABLE IX 


ANALYSIS 0? VARIANCE 

ARCSIN-TRANSFORhED T6ee RECOGNITION ACCURACY 

WITHOUT REJECTS 

Y = 2 - ARCSIN [SORT(ACCURACY %)] 


SOURCE 

SS 

df 

MS 

F 

P 

BETWEEN SUBJECTS: 

0.S64 

19 




Typing Ability 
(TA) 

0.001 

1 

0.001 

0.02 

NS 

3rrcr 

0.663 

18 

0.048 



WITHIN SUBJECTS: 

1.033 

100 




Data Entry 

Mode (DSM; 

0.000 

' 1 

0.000 

0 .00 

NS 

TA I DEM 

0.009 

1 

0.009 

0.69 

NS 

Error(1) 

0.231 

18 

0.013 



Trials (Tr) 

0 .009 

2 

0.005 

0.63 

NS 

TA I Tr 

0.037 

2 

0.019 

2.38 

NS 

Error(2) 

0.261 

36 

0.008 



DEM. X Tr 

0.053 

2 

0.027 

2 .45 

NS 

TA I DEM I Tr 

0.032 

2 

0.016 

1 .45 

NS 

Error(3) 

0.381 

36 

0.011 



TOTAL 

1.697 

119 





[ NS: NOT SIGNIFICANT for p < 0.05 ] 


66 



TABIS X 


ANALYSIS C? VARIANCE 

ARCSIN-TRANSFOR^’ED RECOGNITION ACCURACY 

'*ITH REJECTS 

Y = 2 * ARCSIN [SORT(ACCURACY %)] 


SOURCE 

SS 

df 

MS 

Y 

P 

BETWEEN SUBJECTS: 

0 .926 

19 




TyDin^ Ability 
(TA) 

0.000 

1 

0.000 

0.00 

NS 

Error 

0.926 

16 

0.051 



WITHIN SUBJECTS: 

1.106 

100 




Bata Entry 

Mode (DEM) 

0.000 

1 

0.000 

0.00 

NS 

TA X DEM 

0.004 

1 

0.004 

0 .33 

NS 

Error(1) 

0.224 

18 

0.012 



Trials (Tr) 

0.001 

2 

0.000 

0 .00 

NS 

TA I Tr 

0.034 

2 

0.017 

2 .43 

NS 

Err or(2 ) 

0.256 

36 

0.007 



DEM X Tr 

0 .046 

2 

0.023 

1.64 

NS 

TA X DEM X Tr 

0.018 

2 

0.009 

0.64 

NS 

Error(3) 

0.521 

36 

0.014 



TOTAL 

1.977 

119 




[ NS : 

NOT SIGNIFICAN 

T for 

p < 0.05 ] 




87 





















During the experirent the author observed that 
subjects occasionally became frustrated when the 
T600 was misrecognizing their utterances. This 
frustration appeared to, at times, generate a lack of 
confidence in the T600, along with a change in the 
overall pitch, rate, and inflection of the voice. 
The frustration seemed more prevalent in the 
unbuffered than the buffered mode. ?or this reason, the 
T600 buffered mode was expected to have a better 
recognition rate, since it was faster and somewhat easier 
to use. However the results indicate there is no 
difference in the recognition rate. One explanation is that 
subjects went faster in the buffered mode since they could 
correct the misrecognitions more easily. With the 
consequence of a misreccgnition reduced, they were less 
afraid to make mistakes. 

5. Results for Subject Attitudes 

The scores from the subjective questionnaire given 
before and after the experiment were tested for any general 
change in opinion regarding voice versus typed data entry. 
These scores were evaluated using a two-tailed nonparametric 
sign test, flc = 0.10. A significant snift in favor of voice 
data entry over typing occured for half of the criteria 
covered by the questionnaire. No significant shifts toward 
typing resulted from the analysis. Appendix I contains the 
results of the pre/post questionnaire. 


88 



S uirrnar i z ins the results, subjects either were 
neutral or favored voice before and after the eiperirT:ent. 
After the experiment, they preferred voice even more for 
ease of use, speed, flexibility, intermittent use, and 
finally ease of learning to use as an input modality. They 
continued to believe that voice was a more accurate, 
sustaining, relaxed man-machine interface fcr on-line 
reporting of critical, tine-sensitive information such as 
intelligence obtained in a high-pressure work environment. 

The subjects' positive attitudes about voice arise 
from their fresh experience and observations of speech 
recognition equipment in the C3 Lab at NPS, where it is used 
with the Wargame Effectiveness Simulator (WES) with graphics 
and other ARPANET and laboratory facilities to demonstrate 
its potential for command, control, and communications 
applications. 


S9 
























III. DISCUSSION 


A. DEMRAL 

This thesis investigated tne potential application of 
automatic speech recognition technology to military imagery 
interpretation reporting. Only the order of tattle portion 
of reporting was investigated because of limited time and 
resources. The overall results of the experiment are 
supportive of the application of voice data entry for 
imagery interpretation reporting systems. Voice-buffered 
mode was 58% faster than typing, while voice-unbuffered was 
41% faster. On the average, voice was 50% faster than 
typing. 

Voice was faster because it allowed the operator to view 
the image while reporting. This experiment modeled 
conventional imagery reporting systems where a light table 
is located next to a computer console. The operator 
must move back and forth between the light table and the 
console, or two operators work together, with one 
interpreting the imagery, and the other writing the report 
via the console. For these situations, it appears voice 
data entry would significantly improve reporting speeds 
and/or require only one person per station to perform the 
task. For never systems with the keyboard and function keys 
built into a computer console with a light table or digital 


90 







displa/, voice na/ aot have as significant an irrpact for 
improvin? reporting speeds. 

Both voice and typing were very accurate for 
the experimental task, with no significant difference 
letveen modes and an overall accuracy of 99.5%. It is 
interesting - to note these speeds and accuracies were 
obtained even though subjects were less efficient with 
either mode of voice. Voice-unbuffered had 80.1% 
efficiency, voice-buffered had 65% efficiency, and 
typing had 95% efficiency. These results were all 
attained at a significance level of x = 0.05 or better. 

In terms of recognition accuracy, the results were 
tetter tnan the author expected. Poorer results were 
expected because short phrases consisting of several 
utterances were used rather than simple one or two utterance 
commands. It was anticipated that subjects would run words 
together more than they actually did, and it was also 
anticipated that the Te00 would have more trouble with 
similar sounding terms such as MICt-25 FOXBAT and f^IG-25R 
?0XEAT...or CEARLIZ I CLASS and CHAHLIF II CLASS. Though 
the 1500 did misrecognize such words at times, subjects 
quickly adapted to the situation, emphasizing the portion of 
the utterance that was unique, thereby achieving 
better results. The 97% overall recognition accuracy 
would likely improve with practice and increased usage. 
Additionally, new high-speed recognition systems, like 


91 


1 

4 

i 


m 


m 


4 


m 


Threshold's QUICLTALK (Trademark), require a much shorter 
pause between utterances, thus permitting the operator to 
speak faster. QUICKTALL is advertised to reach speeds of 
16? vords-per-minute, and 99^ accuracy for moderately 
trained speakers. Vocabulary structuring may also be 
performed which allows the system to search only a subset of 
the vocabulary, thus increasing the speed and accuracy of 
recognition. This system, as advertised, has twice the 
speed of the T600 used in the experiment. 

Subjects tendea to prefer voice before and after the 
experiment (even more). For tne vast majority of subjects, 
this was the first use of voice continuously for an extended 
period of time. Even though it did not meet some of their 
more lofty expectations, they continued to give voice the 
edge in the subjective questionnaire, and actually 
strengthed their opinions toward it on several criteria. 

Thus this experiment, though outside an operational 
setting, supports further research and possible applications 
of ASR for imagery interpretation reporting systems, and 
perhaps other similar intelligence and tactical cc^mand end 
control data systems. The results are certainly not new, 
but add credence to the related results achieved by RADC, 
NFS, and others. 

Use of the ARPANET facilities in this 
experiment demonstrated, to a limited degree, that 
reporting can be performed without the benefit of a 


92 


local host computer. This may be very beneficial in the 
future if department of defease organizations want to 
remctely query cr update a ccmmcn data base. 

E. RICOrfiENDATICNS 
1. Research 

The time is perhaps ripe for the military to perform 
some research using voice data entry as a keyboard assist 
for one or mere of the current imagery reporting systems, 
such as TIPI IIS, f^AH.RZS, CATIS, PACZR, AIRZS, and others. 
Ey beginning now to look at the use of voice fer these 
systems, the intelligence community may be able to identify 
the specific questions needing to be addressed to most fully 
adapt voice as an input mcdality. In the next five cr ten 
years, the outlook for "matter-of-fact" use of voice is 
good. By studying the problems associated with training, 
user acceptance, physical interfacing, vocabulary size, 
vocabulary data-base maintenance, respense times, and other 
areas now, voice will be more easily applied later. 

Additionally, voice input may be applied to other 
tasks associated with the other intelligence disciplines 
using interactive computer-controlled devices. Command 
center applications are also receiving increased attention 
as natural language query systems coupled with graphics 
displays commanded by voice are now a reality in terms of 
advanced applications technology. 


93 







All new irr.agery exploitation s/sterrs being developed 
or o’Cdified snculd fully consider the benefits of voice 
recognition technology. Considering the three to eight years 
it takes to develop a new syster;, it is highly likely that 
by the time it is fielded, significantly more voice 
capabilities will be available. Special consideration 
should be given to not only to how it might aid interpreters 
in the reporting process, but also how they might be able to 
use it to enhance, manipulate, annotate, and otherwise 
modify digital softcopy imagery on systems such as Compass 
Preview. 

2. Applications 

Practical applications using voice data entry on a 
large scale will require a significant amount of work. It 
must also be proven that while voice may be as fast or 
faster than typing that the time differential achieved 
contributes commensurately with the additional cost of such 
new technology. Careful attention must be paid to involving 
the users, since they will ultimately "sell" the system, 
even though proven in the lab. 

The author recommends a small application first with 
a few of the best interpreters who know the imagery 
system well, and are ambivalent regarding voice data entry. 
Py allowing them to use voice on a daily basis, they can 
develop the in-house expertise at the level needed to apply 
it on a large scale later...or they may be able to assess 


94 




that it just won't work for that particular application. 

The oiilitary is fortunate, having excellent research 
people involved with voice technolo,ey. RADC and NFS are 
just two military institutions able to provide consultation 
and assistance. 

C. CONCLUSIONS 

Since 1972, automatic speech recognition has 


proven to 

be 

valuable for 

a number 

of limited 

applications . 

The 

future for the 

technclogy 

is bright. 


The author concludes voice is not only feasible, but 
desirable as a means toward the best imagery 
interpretation reporting possible. It is not so much a 
question of whether voice can be used, but rather ... 
how can it be used?...how extensively can it be used?...and 
how cost-effective will it be? 


95 












































APP2NDIX A 


USSR/WARSAW PACT ORDER Of BATTLE (OB, VOCABULARY 


INSTRUCTIONS: TRAIN TEE WORDS IN THE GIVEN SEQUENCE, USING 
TEE GIVEN PROMPT. WORD NUMBERS MARKED WITH AN ASTERISK MAY 
EE TRAINED WITH THE GIVEN PROMPT OR YOU MAY USE YOUR OWN. 
(THESE WORDS WILL BE USED fOR TEXT EDITING, AND THUS SHOULD 
BE FAMILIAR, EASY TO REMEMBER) BE SURE TO WRITE IN THE 
ONE THAT YOU USE ON TEE VOCABULARY LISTING SO THAT YOU MAY 
HAVE IT FOR FUTURE REFERENCE. 


WORD 

PROMPT 

OUTPUT 


ZERO 

0 

1 

ONE 

1 

2 

TWO 

c 

3 

THREE 

3 

4 

FOUR 

4 


FIVE 

c. 

5 

S IX 

6 

7 

SEVEN 

7 

6 

EIGHT 

8 

9 

NINE 

9 

10 

ALPHA 

A 

11 

BRAVO 

B 

12 

CHARLIE 

C 

13 

DELTA 

D 

14 

ECHO 

E 

15 

FOXTROT 

A 

16 

GOLF 

G 

17 

HOTEL 

H 

18 

INDIA 

I 

19 

JULIET 

J 

20 

KILO 

K 

21 

LIMA 

L 

22 

MIKE 

M 

23 

NOVEMBER 

N 

24 

OSCAR 

0 

25 

POPPA 

P 

26 

QUEBEC 

Q 

27 

ROMEO 

R 

28 

SIERRA 

S 

29 

TANGO 

T 

30 

UNIFORM 

U 

31 

VICTOR 

V 

32 

WHISKEY 

w 

33 

XRAY 

X 


96 







til 












34 

YANKE3 

Y 

35 

ZULU 

Z 

36 

POSSIBLI 

POSSIBLE 

37 

PROBABLE 

PROBABLE 

36 

COMFIRhSD 

_CONFIRMED_ 

39 

DASH 

- 

40- 

IRAS Z 

BKSP <CTRL A> 

41 

GO OR CARRIAGE RETURN 

^CARRIAGE RETUR 

42 

SLASH 

/ 

43- 

KILL IvORD 

<CTRL V> 

44* 

KILL LINE 

<CTRL X> 

45* 

REPEAT LINE 

<CTRL R> 

46 

SPACE 

<SPACE CHARACTE 

47 

TEN 

10 

46 

INSTALLATION 

INSTALLATION 

49 

ELEVEN 

11 

50 

UPPER LEFT 

UPPER LEFT 

51 

TANKS 

TANKS 

52 

LIGHT 

LIGHT 

K"? 

W W 

MEDIUM 

MEDIUM 

54 

HEAVY 

HEAVY 

55 

T72 

T-72 

56 

Tc2 

T-62_ 

57 

T54/55 

T—54/55 

56 

T10 

T-10 

59 

T34/65 

T-34/85 

60 

TWELVE 

12 

61 

PT76 

PT-76 

62 

AMPHIBIOUS 

AMPHIBIOUS 

63 

UPPER RIGHT 

UPPER RIGHT 

64 

APC 

APC 

65 

AT GW 

ATGW 

66 

ERDM 

BRDM 

67 

BTR6ePK 

BTR-60PK 

68 

BMP76PB 

BMP-76PB 

69 

ETR152 

BTR-152 

70 

ETR50PK 

BTR-50PS 

71 

FIELD HWTZRS 

FIELD HOWITZERS 

72 

ASU65 

ASU-&5 

73 

SU100 

SU-100 

74 

AIRBORNE 

AIRBORNE 

75 

LOWER LEFT 

LOWER LEFT 

76 

D3e 

D-30 

77 

AT3 SAGGER 

AT-3 SAGGER 

78 

ANTI-TK GUNS 

ANTI-TANK GUNS 

79 

D74 

D-74 

£0 

B20 

D-20 

61 

M1955 

M-1955 

82 

D44 

D-44 

63 

EM21 

EM- 2 I 

64 

M1976 

M-1976 


97 


65 

be 

67 

66 

69 

90 

91 

92 

93 

94 

95 

96 

97 

96 

99 

100 

101 

102 

103 

104 

105 

106 

107 

10S 

109 

110 

111 

112 

113 

114 

115 

116 

117 

118 

119 

120 

121 

122 

123 

124 

125 

126 

127 

126 

129 

130 

131 

132 

133 

134 

135 


3f^24 

EM-24 

f?.0G3 

FROG-3 

FH0G4 

FROG-4 

FR0G7 

FROG-7 

SCUD A 

SCUD-A 

SCUD E 

SCUD-E 

SS12 SCL3RD 

SS-12 SCALSBOAED 

SSM 

SSM 

ATI SNAPPIR 

AT-1 SNAPPER 

65 MIDIMETER 

85-MM 

100 MILIMETR 

100-MM 

SA4 GANZF 

SA-4 GANEF 

SA6 GAINFUL 

SA-6 GAINFUL 

SA6 GECKO 

SA-6 GECKO 

SA9 GASKIN 

SA-9 GASKIN 

LAUNCHERS 

LAUNCHERS 

THIRTEEN 

13 

ASW 

ASW 

FOURTEEN 

14 

AA GUNS 

AA GUNS 

FIELD GUNS 

FIELD GUNS 

ZU23/2 

ZU-23/2 

ZSU23/4 

ZSU-23/4 

ZSU57/2 

ZSU-57/2 

S60 

s-6e 

M44 

M-44 

M49 

M-4 9 

57 MILIMETER 

57-MM 

SU15 FLAGON 

SU-15 FLAGON 

YAK28P FRBAR 

TAK-2SP FIREEAR 

TU28P FIDLR 

TU-28P FIDDLER 

MIG19 FARMER 

MIG-19 FARMER 

MIG21 FSHBED 

MIG-21 FISHBED 

MIG23 FLGGSR 

MIG-23 FLOGGER 

MIG25 FOXBAT 

MIG-25 FOXBAT 

MIG27 FLGGER 

MIG-27 FLOGGER 

TU20 BEAR 

TU-20 BEAR 

TU126 MOSS 

TU-126 MOSS 

SU9 FISHPOT 

SU-9 FISHPOT 

MIG25R FXBAT 

MIG-25R FOXBAT 

TU22 BLINDER 

TU-22 BLINDER 

TU16 BADGER 

TU-16 BADGER 

TU26 BACKFIR 

TU-26 BACKFIRE 

MI4 HOUND 

MI-4 HOUND 

MI12 HOMER 

MI-12 HOMER 

MI6 HOOK 

MI-6 HOCK 

MI6 HIP 

MI-6 KIP 

MI10 HARKE 

MI-10 HARKE 

Mi 124 HIND 

MI-24 HIND 

IL38 MAT 

IL-38 MAY 

M-4 BISON 

M-4 BISON 


96 







136 

137 

136 

139 

142 

141 

142 

143 

144 

145 

146 

147 

148 

149 

150 

151 

152 

153 

154 

155 

156 

157 

156 

159 

160 

161 

162 

163 

164 

165 

166 

167 

168 

169 

170 

171 

172 

173 

174 

175 

176 

177 

178 

179 

180 

161 

162 

183 

184 

185 

186 


SU19 FENCE?. 
FIFTEEN 
AN8 CAFP 
AN 12 CUB 
AN22 COCK 
AN26 CURL 
KA15 HEN 
KA18 HOG 
KA25 HORMONE 
IL12 COACH 
IL14 CRATE 
IL28 BEAGLE 
IL76 CANDID 
AWACS 
BE12 MAIL 
TRANSPORTS 
FIGHTERS 
BOMBERS 
FIGKTER-BMRS 
STRIKE/ATTCK 
HELICOPTERS 
RECONNAISNC 
SS 

FRIGATE 

SSB 

SSGN 

SSBN 

CARRIER 

CRUISERS 

DESTROYERS 

MINESWEEPERS 

FRIGATES 

CORVETTES 

MISSLE 

TORPEDO 

BOATS 

LANDING 

SIXTEEN 

INTELLIGENCE 

SHIPS 

SEVENTEEN 

EIGHTEEN 

KIEV CLASS 

MOSKVA CLASS 

SSN 

DELTA CLASS 
DELTA2 CLASS 
H0TEL2 CLASS 
HOTELS CLASS 
ASU57 

VICTOR CLASS 


SU-19 FENCSR 

15 

AN-e CAMP_ 

AN-12 CU3_ 

AN-22 COCK_ 
AN-26 CURL_ 
^A-15 HEN_ 

KA-IS EOG_ 

KA-25 HORMONE_ 
IL-12 CCACK_ 
IL-14 CRATE_ 
IL-2S BEAGLE_ 
IL-76 CANDID_ 
AWACS 

BE-12 MAIL_ 
TRANSPORTS 
FIGHTERS 
BOMBERS 

FIGHTER-BOMBERS 

STRIKE/ATTACK 

HELICOPTERS 

RECONNAISSANCE 

SS 

FRIGATE 

SSB 

SSGN 

SSBN 

CARRIER 

CRUISERS 

DESTROYERS 

MINESWEEPERS 

FRIGATES 

CORVETTES 

MISSLE, 

TORPEDO, 

BOATS 

LANDING, 

16 

INTELLIGENCE, 

SHIPS 

17 

16 

KIEV CLASS, 
MOSKVA CLASS, 
SSN 

DELTA CLASS, 
DELTA II CLASS, 
HOTEL II CLASS, 
HOTEL III CLASS 
ASU-57, 

VICTOR CLASS 


99 


■.« 

i 

i 




187 

ise 

1S9 

19 0 

191 

192 

193 

194 

195 

196 

197 

198 

199 

200 

201 

202 

203 

204 

205 

206 

207 

208 

209 

210 

211 

212 

213 

214 

215 

216 

217 

218 

219 

220 

221 

ccc 

223 

224 

225 

226 

227 

22S 

229 

230 

231 

232 

233 

234 

235 

236 

237 


TANKZE CLASS 
GOLFl CLASS 
G0LF2 CLASS 
ZULU4 CLASS 
KRZSTAl CLAS 
:<HZSTA2 CLaS 
hlRAAl CLASS 
MIRKA2 CLASS 
PETYAl CLASS 
PETYA2 CLASS 
JULIET CLASS 
LOWER RIGHT 


YANKEE CLASS_ 
GOLF I CLASS, 
GOLF II CLASS, 
ZULU IV CLASS 
KRSSTA I CLASS, 
KRESTA II CLASS 
hiRKA I CLASS, 
MIRKA II CLASS, 
PETYA I CLASS, 
PETYA II CLASS, 
JULIET CLASS, 
LOWER RIGHT 


122 MILIMETR 

122-MM 

FOXTROT CLAS 

FOXTROT CLASS 

ROMEO CLASS 

ROMEO CLASS 

SSG 

SSG 

BRAVO CLASS 

BRAVO CLASS 

ECEOl CLASS 

ECHO I CLASS 

SCH02 CLASS 

ECHO II CLASS 

152 MILIMETR 

152-MM 

TANGO CLASS 

TANGO CLASS 

WHISKEY CLAS 

WHISKEY CLASS 

CEARLIEl CLS 

CHARLIE I CLASS 

CHARLIE2 CLS 

CHARLIE II CLASS 

KARA CLASS 

KARA CLASS 

SVERDLOV CLS 

SVERDLOV CLASS 

KYNDA CLASS 

KYNDA CLASS 

KRIVAK CLASS 

KRIVAK CLASS 

KASHIN CLASS 

KASHIN CLASS 

240 MILIMETR 

240-MM 

KANIN CLASS 

KANIN CLASS 

INTERCEPTORS 

INTERCEPTORS 

KOTLIN CLASS 

KOTLIN CLASS 

KOTLN SAM CL 

KOTLIN-SAM CLASS 

SKORY CLASS 

SKORY CLASS, 

RIGA CLASS 

aIGa CLASS 

GRISHA CLASS 

GRISHA CLASS 

NANUCKKA CLS 

NANUCHKA CLASS 

POTI CLASS 

POTI CLASS 

OSAl CLASS 

OSA I CLASS 

0SA2 CLASS 

OSA II CLASS 

KOMAR CLASS 

KOMAR CLASS 

STENKA CLASS 

STENKA CLASS 

NINETEEN 

19 

TWENTY 

20 

SHERSHSN CLS 

SHERSHEN CLASS, 

TWENTY-ONE 

21 

NATYA CLASS 

NATYA CLASS 

YURKA CLASS 

YURKA CLASS 

ALLIGATOR CL 

ALLIGATOR CLASS 

POLNOCNY CLS 

POLNOCNY CLASS 


100 








236 

239 

240 

241 

242 

243 

244 

245 

24c 

247 

24S 

249 

250 

251 

252 

253 

254 


T’aENTY-T’aO 

PRIMORYS CIS 

TWINTY-THRZZ 

TWZNTY-ZOUR 

SS16 

SS20 

5514 SCFGOA? 

5515 SCROOGE 
ICEr 

IRBh 
MOBILE 
M240 
MORTARS 
ASSAULT GUNS 
ROCKET LCHRS 
AIRCRAFT 
TWENTY-FIVE 


22 

PRIMORYE CLASS, 

23 

24 

ss-ie_ 

SS-20_ 

SS-14 SCAPEGOAT, 
SS-15 SCROOGE, 

I CBM 

IRBM 

MOBILE 

M-240 

MORTARS 

ASSAULT GUNS 

ROCKET LAUNCHERS 

AIRCRAFT 

25 


101 







APPENDIX 3 


SCENARIO CARDS 

TYPING CARDS ->>>>>>>> FIRST TWELVE 


installation 0613-T11214 

I 

** 4 CONEIRMED 3MP-76PB APC 

7 CONEIRNiSD BRLM APC 

I 

3 CONFIRMED AT-3 SAGGER ATGW ** 

4 PROBABLE ZSU-23/4 AA GUNS 


j 

40 CONFIRMED T-54/55 MEDIUM TANKS ** 

j V 'T' 

4 PROBABLE SA-9 GASKIN LAUNCHERS 

I 

I 

I 

I 

I 

6 PROBABLE ZU-23/2 AA GUNS 

_I __ 

I ” “ 


INSTALLATION 0115-T12314 

5 CONFIRMED M-4 BISON BOMBERS 

j 

** 1 POSSIBLE TU-2e BEAR RECONNAISSANCE 


AIRCRAFT 


12 CONFIRMED TU-20 BEAR BOMBERS 

1 CONFIRMED TU-126 MOSS AWACS 

i 

_I_ 

2 CONFIRMED BE-12 MAIL RECONNAISSANCE 
AIRCRAFT i 

I 

7 CONFIRMED IL-2b BEAGLE BOMBERS 
17 CONFIRMED TU-IS BADGER BOMBERS ** 


3 PROBABLE TU-16 BADGER RECONNAISSANCE 
AIRCRAFT 


102 






INSTALLATION 0128-T13213 

! / 

2 CONFIRMED KHESTA II CLASS CRUISERS 

3 CONflRMED ERESTA I CLASS CRUISERS 

1 

1 POSSIBLE TANGO CLASS SS 
> 

I 

1 

j 

--"l2"CCNFrRMED“WErSKlY"CLASS“SS 

I 

2 PROBABLE CEARLIE ll CLASS SSGN 

1 

I 

S 

I 

j 

1 CONFIRMED CHARLIE I CLASS SSGN 




I 

I 

I 


1_______I__ _—______ 

I INSTALLATION 0298-T14218 
I } 

I 50 CONFIRMED ASU-65 AIRBORNE ASSAULT GUNS 

I j 

1 27 CONFIRMED ASU-57 AIRBORNE ASSAULT GUNS 

I I 

[ 1 

I I 

I I 

I i 

I I 

I_i_I_ 

I t 

I 20 POSSIBLE M-240 HEAVY MORTARS 

1 j 

162 PROBABLE 122-MM D-30 FIELD HOWITZERS 

i I 

1 I 

j I 

146 CONFIRMED 240-MM EM-24 ROCKET LAUNCHERS 

1 i 

I I 

I JU I 

____ 1 ....._......___ 

I 


103 








INSTALLATION 0S27-T21253 
6 CONFIRMED FOXTROT CLASS SS 

I 

12 CONFIRMED JULIET CLASS SSG 
** 2 PROBABLE DELTA II CLASS SSEN 

j 

3 PROBABLE DELTA CLASS SSBN 

I 

I 

”CONHRMSD"GOLf I l”CLASS”SS 

I 

I 

j 

5 CONBiRMEi} POTI CLASS CORVETTES 

I 

I 

2 POSSIBLE YANKEe'cLASS SSBN 

I 

7 PROBABLE ROMEO CLASS SS 


INSTALLATION 0405-T22217 
40 CONFIRMED T-10 HEAVY TANKS 

I 

57 CONFIRMED T-34/85 MEDIUM TANKS 
43 CONFIRMED T-54/55 MEDIUM TANKS 


I 

I 

_I_ 

3 CONFIRMED PT-76 LIGHT AMPHIBEOUS TANKS 

j 

e CONFIRMED BTR-152 APC 

I 

j 

6 CONFIRMED BRDM RECONNAISSANCE APC 


104 








INSTALLATION •2352-T23224 ** 

I / 

11 CONflRMEL TU-22 BLINDER BOMBERS 

I 

I 

20 CONJIRMSD TU-2e BACKFIRE BOMBERS 

5 probable IL-28 BEAGLE BOMBERS 

{ >!£# 


2 CONFIRMED IL-76 CANDID TRANSPORTS 

I 

I 

j *Sr 

15 CONFIRMED AN“12 CUB TRANSPORTS 

I 

I 

j SrS}* 

7 CONFIRMED MI-8 HIP HELICOPTERS 


_____ _ _ • _ __—__—__ 


INSTALLATION 0247-T24283 

5 probable koi^ar'class i^issle boats 


17 CONFIRMEE OSA I CLASS MISSLE BOATS 

I 

5 CONFIRMED OSA Il'cLASS MISSLE BOATS 

! 


I 

I 

j 

7 CONFIRMED STENKA CLASS TORPEDO BOATS 


I 

I 

j 

11 POSSIBLE NANUCHKA CLASS TORPEDO BOATS 

I 

6 POSSIBLE GRISHA'class CORVETTES 
2 PROBABLE SHSRSHEN CLASS TORPEDO BOATS*- 


105 






















1 INSTALLATION 0243-T31£7£ 
j j 

! 12 CONFIRr^ED MIG-27 FLCGGZR STRIKE/ATTACK 
1 AIRCRAFT I 

il6 CONFIRMED SU-19 FENCER STRIKE/ATTACK 
i AIRCRAFT I 

I I 

! 2 POSSIBLE MIG-25R FOXEAT RECONNAISSANCE 

1 AIRCRAET ** ! 


** 1 CONFIRMED IL-38 MAY ASV AIRCRAFT 

{ 

3 CONFIRMED AN-6 CAMP TRANSPORTS 

t 

I 

5 CONJIRNSD AN-26 CURL TRANSPORTS 

j 

I 

I 

_I___ 


INSTALLATION 0657-T32179 ** 

I / ** 

2 CCNFIRMPD HOTEL II CLASS SSBN / 

1 CONFIRMED HOTEL III CLASS SSBN 

I 

I 

I 

I 

I 

I 


_I_ 

[ 

1 PROBABLE GOLF I CLASS SSB 
1 PROBABLE MIRKA I CLASS LIGHT FRIGATE 

I 

I 

j 

1 POSSIBLE ZULU IV CLASS SS 

! 


I 


106 



















INSTALLATION 0410-T33252 

** 4 CONFIRMED 100-MM M-49 AA GUNS 

4 CONFIRMED ZSU-57/2 AA GUNS --- 

6 CONFIRMED 65-MM M-44 AA GUNS 

I ## 

j 

/ ! 

8 CONFIRMED FROG-4 SSM MOBILE LAUNCHERS 

I 

_ ___I __ 

I 

j 

6 PROBABLE AT-1 SNAPPER ATGW 

I 

*5^ j 

4 CONFIRMED 122-MM D-74 FIELD GUNS 

I 

I 

21 CONFIRMED 85-MM D-44 ANTI-TANK GUNS 

_I_ 

I 


INSTALLATION 0173-T34246 
1 CONFIRMED TU-126 MOSS AWACS / 

1 CONFIRMED TU-16 BADGER RECONNAISSANCE 
AIRCRAFT ! 

16 CONFIRMED AN-22 COCK TRANSPORTS 

>!s5it { 

I 


18 CONFIRMED TU-20 BEAR BOMBERS 

/ 




12 CONFIRMED TU-22 BLINDER BOMBERS 


2 CONFIRMED TU-20 BEAR RECONNAISSANCE 


AIRCRAFT 


! ❖’i' 


107 











VC ICI- 


UNBUFFERED CARDS -> > > NEXT TWELVE 


INSTALLATION glSe-VllLSC 

I / 

9 probable YAK-28P_FIREBAR fighter-boneers 

** 12 CONFIRrSD SU-15_FLAG0N INTERCEPTORS 

20 CONFIRMED TU-28P_FIDDLER INTERCEPTORS 

j ## 

j ** 

T3“PR0£ABLE"F!Ig-25“F0XBAT“InTERCEPTCRS 


11 POSSIBLE SU-9_FISEP0T FIGHTERS 

I 

I 


15 PROBABLE MIG-21_FISHBED FIGHTERS** 

_I___ 


INSTALLATION 0357-V12252 

j 

1 CONFIRMED MOSKVA_CLASS CARRIER 

I 

Sjc# I 

1 CONFIRMED KIEV_CLASS CARRIER 

** 2 PROBABLE KARA_CLASS CRUISERS 

I 

__________ ^ _____________________ 

** 3 CONFIRMED KASEIN_CLASS DESTROYERS 

** 4 CONFIRMED KRIVAK_CLASS FRIGATES 

>!«={! j 

8 CONFIRMED MIRKA_II_CLASS LIGHT FRIGATES 


108 




















_I___ 

INSTALLATION 0168-V13259 
6 probable S-60 l^;ZDIUM AA GUNS 

I 

4 CCNFIRI^ED SA-8_GZCK0 LAUNCHERS 

I 

I 

I 

3 CONFIRMEL SA-4^GANEF LAUNCHERS 

I 

I 

I 

_I___ 

:Jc3;s I ^ - 

4 CONFIRMED SA-6^GAINFUL LAUNCHERS 

I 

3 CONFIRMED SS-12_SCALEBGARD MOBILE SSM 

I 

5 CONFIRMED FROG-3 MOBILE SSM 

I 

I 

I 

4 CONFIRMED SA-9^GASKIN LAUNCHERS 

— —_ j _ __ — 


INSTALLATION C199-V14197 

I jjcsie 

le CONFIRMED MI-4 HOUND HELICOPTERS 


>!!# I 

11 CONFIRMED MI-12_E0MER HELICOPTERS 

I 

** 5 PROBABLE MI-6 HOOK HELICOPTERS 


[ *>!! 

21 CONFIRMED MI-10 EARKE HELICOPTERS 


Jltsie 


19 PROBABLE MI-24 HIND HELICOPTERS 

I 
I 
I 
I 

___I _____ 


109 







INSTALLATION 02e6-V21221 

I :jt# 

1 CONFIEMSL SS-ie MOBILE ICEM 

j 

** 1 POSSIBLE SS-lb_SCROOGE MOBILE IRBM 
1 CONFIRMED SS-14_S CAPEGO AT MOBILE IRBM 
2 probable SS-20 MOBILE IRBM 


** 1 CONFIRMED FROG-7 SSM 

** 3 CONFIRMED SCUD_A SSM 

I 

I 


I 

1 POSSIBLE SCUD_B SSM 

I 
I 
I 

I 


INSTALLATION 0195-722231 


10 CONFIRMED KA-25_H0RM0NE HELICOPTERS 

] ~ 

[ 

11 CONFIRMED MI-S HIP HELICOPTERS 

T 

I 
I 
I 
I 

_I_ 

I 

4 CONFIRMED KA-i5_HEN HELICOPTERS 
6 CONFIRMED KA-18 HOG HELICOPTERS 


23 CONFIRMED IL-12 COACH TRANSPORTS 


22 CONFIRMED IL-14_CRATE TRANSPORTS ** 

___ I ___ 


110 







INSTALLATION 0327-V23249 

2 PRCBAEIE PRIN’ORYE CLASS INTELLIGENCE 
SHIPS ! 

I 

I 

3 CCNElRt^.ED POLNOCNY.CLASS LANDING SHIPS 
2 CONFIRMED ALLIGATOR_CLASS LANDING SHIPS 

! 


I 

_ \ _ 

I 

3 CONFIRMED YUHKA_CLASS MINESWEEPERS 

I 

5;:5;s } 

2 POSSIELE NATYA^CLASS MINESWEEPERS 
4 PROBABLE PETYA^I^CLASS FRIGATES 

I 

I 

I 

_ I_ 


_j_ 

INSTALLATION 01S7-V24Z77 

60 CONFIRMED BTR-60PK AMPHIBEOUS APC 
25 CONFIRMED T-62 MEDIUM TANKS 

I 

23 CONFIRMED SS-MMi I)-44 ANTI-TANK GUNS 


I 

IS PROBABLE BM-21 ROCKET_LAUNGEERS 

1 

__I_ 


I 

«*22 CONFIRMED 122-MM D-3e FIELD_HOWITZERS 

I 

1 

5JC5}; j 

19 CONFIRMED M-1955 FIELD^HOWITZERS 

I 

17 CONFIRMED M-1976 AIRBORNE 
ASSAULT GUNS i 


111 






I i 


_j_ 

INSTALLATION 0528-V31176 

I 

** 11 CCNFIEMED PETYA_II_CLASS FRIGATES 
2 PROBABLE 3RAV0_CLASS SS 

I 

I 

j 

3 CONFIRMED ECHO_I_CLASS SSGN 

I 

___I_ 


j JjCJiS 

12 CONFIRr^ED ICHC^I I^CLASS SSGN 

j 

5 CONFIRriD RIGA.CLASS FHIGATIS 


I 

I 


1 


i INSTALLATION 

0410-732237 

❖ j 

1 22 

CONFIRMED 

BTR-50PK AMPEIBEOUS 

APC ! 

! 40 

CONFIRMED 

T-72 HEAVY TANKS -- 

j 

1 IB 

PROBABLE SU-100 ASSAULT GUNS 




I 


j **£,5 

CONFIRMED 

152-MM D-20 FIELD, 
« 

HOWITZERS I 


j 

24 CONFIRMED 100-MM M-1955 FIELD GUNS 


I 

I 

[ 

13 PROBABLE M-1976 AIRBORNE ASSAULT^GUNS 

I 

I 

I 

I 

I 

I 

_I_ 

I 


112 







i INSTALLATION 

0276-V33264 


1 15 CONFIRMED 

MIG-21 FISHBED 

FIGHTERS ! 


j 

1 

1 

j 

112 CONFIRMED MIG-19_FARMER FIGHTER-BOMBERS! 

1 ! i 

|*’i‘ 11 PROBABLE 

» 

MIG-23 FLOGGSR 

1 

1 

FIGHTERS i 


I J>:5;s 

17 CONFIRMED MIG-£7_fLOOSER STRIKE/ATTACK 
AIRCRAFT 1 




21 CONFIRMED MIO-25 FOXBAT INTERCEPTORS 

T 


3 POSSIBLE TD-28P FIDDLER INTERCEPTORS 


INSTALLATION 0362-V34273 

I 

** 2 PROBABLE SKORY^CLASS DESTROYERS 

I 

3 CONFIRMED KOTLIN_CLASS DESTROYERS 

i 

2 CONFIRMED KYNDA_CLASS CRUISERS 
5 CONFIRMED KANIN CLASS DESTROYERS 

I ^ 

— ^ 

I 


2 CONFIRMED SVERDLOV CLASS DESTROYERS 


❖ sis 




I 

I 

I 

I 


2 PROBABLE SHERSHEN^CLASS TORPEDO BOATS 

I 

4 CONFIRMED KOTLIn’saM CLASS DESTROYERS 


1 

I 


❖❖ 


113 






i 


i 





EUi'FIRSr-VCICI CARLS ->>>>> NEXT TWELVE 


I 


1 INSTALLATION 0613-V51214 


4 CONFIRMED BMP-76PE APC 


1 7 CONFIRMED BRDM 

APC ! 

1 i 

!3 CONFIRMED AT-3 SAGGER ATG¥ ** 

1 1 


1 4 PROBABLE ZSU-23/4 

1 1 ' 

AA_GUNS1 

1 1 
i 43 CONFIRMED T-54/5E MEDIUM TANKS 

1 

^ j 


! I 

I I 


4 FROEABLS'SA-9^GASKIM LAUNCHERS 

I 

} 51 ^^ 

6 PROBABLE ZU-23/2 AA^GUNS 

_I_ 

I 


INSTALLATION 0115-V52314 

3 CONEIRNIED M-4_:BIS0N BOMBERS 

1 POSSIBLE TU-20^BEAR RECONNAISSANCE 
AIRCRAFT j 

I 

12 CONFIRMED TU-20_BEAR BOMBERS 

1 CONFIRMED TU-126 MOSS AWACS 

I ^ 

_I_ 

j 

C CONIIR^EI) BS-12_MAIL RECONNAISSANCE 
AIRCRAFT I 


7 CCNEIRMER IL-2S_EEAGLE BOMBERS -- 
1? CONFIRMED TU-16_BADGER BOMBERS 

’i'* 3 PROBABLE TU-16^BADGER RECONNAISSANCE 
AIRCRAFT 


114 






i 


INSTALLATION 012e-V53113 

i / 

2 CONFIRMED SRESTA_II_CLASS CRUISERS 
3 CONIIRMED KRESTA_I_CLASS CRUISERS 

1 POSSIBLE'taNGO.CLASS SS 

I 

I 

I 

I 

I 

'5*"r2"CGNfrRFifD"WHrsZSYlCLASS"SS 

I 

2 PROEAPLZ CHAHLII^il^CLiiSS SSGN 

! 

1 

1 CONFIRMED CHARLIE^I^CLASS SSGN 

j 

I 

I 


_I___ 

INSTALLATION 0298-V54216 

j 3^5 

50 CONFIRMED ASU-a5 AIRBORNE ASSAULT^GUMS 

I 

27 CONfIRM.ED ASU-57 ' AIRBORNE ASSAULT^GUNS 

JicXi I 


I 

I 

I 

_I_ 

1 

20 POSSIBLE M-240 HEAVY MORTARS 
52 PROBABLE 122-MM D-30 FIELD^HOWITZERS 

I 

I 

I 

48 CONFIRMED 240-MM BM-24 ROCKET-LAUNCHERS 

I 

j 

j 


115 







INSTALLATION £827-761253 
6 CCNflRMEr FOXTROT.CLASS SS 

I -V. 

12 CCNFIRMED JULIIT_CLASS SSG 

** 2 PRCEAELE DELTA 11_CLASS SSEN 

T 

3 PROBAELZ DELTA^CLASS SSEN 

1 

1 

4“coneIrn’Sd”golf_I!Iclass“sssn~^^ 

I 

1 

j 

5 CCNEIH^^ED POTI^CLASS CORVETTES 

1 

2 POSSIBLE YANKEE^CLASS SSEN 

I 

7 PROBABLE ROMEO CLASS SS 


______I ______ 

INSTALLATION e405-V62217 

j 

40 CONEIRMSD T-10 HEAVY TANKS 

57 CONFIRMED T-34/65 MEDIUM TANKS 

43 CONFIRMED T-54/55 MEDIUM TANKS 

1 

1 

! 

1 

1 

_I_ 

3 CONFIRMED PT-76 LIGHT AMPHIEEOUS TANKS 

I 

6 CONFIRMED BTR-152 APC 

I 


6 CON5IRMSD BRDM RECONNAISSANCE APC 

I 

I 

I 

1 


I 

I 


116 







INSTALLATION 0352-V63224 


sis# 


1 / 

11 CONJIRMZI) TU-22 BLINDER BOMBERS 


20 CONEIRMED TU-26_BACKFIRE BOMBERS 
5 PROBABLE IL-28_BEAGLE BOMBERS-’’'’^ 

I 

I 

I 

_I_ 

j 

2 CONFIRMED IL-76_CANDID TRANSPORTS 

I 

I 

15 CONFIRMED AN-12,CUE TRANSPORTS 

I 

I 

7 CONFIRMED MI-S HIP HELICOPTERS 

" I 

I 


___I_______ 

INSTALLATION 0247-V642S3 

I 

5 PROBABLE KOMAR^CLASS MISSLE BOATS 

i 

{ 

17 CONFIRMED OSA^I.CLASS MISSLE BOATS 

I 

5 CONFIRMED OSA^II^CLASS MISSLE BOATS 

3^5{C I 


I 

I 

j 

7 CONFIRMED STENKA^CLASS TORPEDO BOATS 

I 

I 

I 

11 POSSIBLE NANUCHKA^CLASS TORPEDO BOATS 

I 

6 POSSIBLE GRISHa'cLASS CORVETTES 
2 PROBABLE SHSRSHEnIcLASS TORPEDO EOATS-^ 

______ I___— 

I 


117 






INSTALLATION 0242-V71278 

5|t# j 

12 CONFIRhSD iNlG-27_FLOGGER STRISE/ATTACK 
AIRCRAFT I 

16 CONFIRMED SU-19_FENCER STRIKE/ATTACK 
AIRCRAFT 1 

I 

2 P0SSI2LE MIG-25R_F0XBAT RECONNAISSANCE 
AIRCRAFT ** I 


1 CONFIRMED IL-38_MAY ASV AIRCRAFT 

❖ sis j 

3 CONnR^^ED AN-9_CAMP TRANSPORTS 

I 

I 

I 

5 CONIIRMEP AN-26^CURL TRANSPORTS 

j 5;s5;s 

I 

I 

_1_ 


INSTALLATION 0657-772179 

j / 

2 CONFIRMSI) HOTEL.II.CLASS SSBN / 

1 CONFIRMED HOTEL III CLASS SSBN 

— 1 — 

I 

I 

I 

I 

I 

I 

I 

_I_ 

[ 

1 PROBABLE GOLF.I^CLASS SSB 

j 

1 PROBABLE MIEKA.I.CLASS LIGHT FRIGATE 

I 

I 

j 

1 POSSIBLE ZULU IV CLASS SS 


I 

I 


lis 
































INSTALLATION 0410-V73252 

** 4 CONFIRr^LD 100-Mr^ M-49 AA_GUNS 

4 CONFIRMED ZSU-57/2 AA_GUNS - 

5 CONFIRMED S5-MM M-44 AA_GUNS — 

I 

I 

J 

/ 

6 CONFIRMED FRCG-4 SSM MOEILE LAUNCHERS 

_I_ 

I 

I 

5!!J!5 j 

6 PROBABLE AT-1_SNAPPER ATGW 

I 

I 

I 

4 CONFIRMED 122-MM D-74 FISLD_GUNS 

I 

I 

j !it« 

21 CONFIRMED 65-MM D-44 ANTI-TANK GUNS 


_______ I _______ 

INSTALLATION 0173-V74246 
1 CONFIRMED TU-126_M0SS AWACS / 

1 CONFIRMED TU-16_BADGSR RECONNAISSANCE 

AIRCRAFT ' 

16 CONFIR^^ZD AN-22^CCCK TRANSPORTS 

j 

I 

I 

I 

I 

I 

_I_ 

le CONFIRMED TU-20 BEAR BOMBERS 

/ I 

j 

I 

12 CONFIRMED TU-22_BLINDER BOMBERS 

I 

I 

I 

2 CONFIRMED TU-20 BEAR RECONNAISSANCE 

AIRCRAFT ^ I 

_____I_____ 

1 


I 


119 


















APPENDIX C 


Te00 TRAINING INSTRUCTIONS 

For this experiment a 254 word vocabulary will be used 
with the Threshold 600 (T600} voice recognition system. You 
will be required to speak each utterance ten times to train 
the Te00 tc recognize ycur voice. Two sessions of 
approximately 90 minutes will be required to complete the 
training prior to experimentation. 

Please observe the following guidelines during training 
and operation of the T600, as they will improve performance 
and reduce the time required for retraining. 

a. Use variety. Say the repetitions with the 
variety of intonation, emphasis, and volume 
you would expect to use in normal speech. 

d. Speak crisply without pausing. 2e natural 
and relaxed. Don't exaggerate or 

overemphasize; for example when saying the 
word "five", don't say "FI-I-VIK", thereby 
overemphasizing the end of the wcrd in an 
unnatural way. 


120 










b. Do the repetitions in e?rcups to avoid breath 
noise and help you count the reps. For 
example to train the word "zero” group the 
zeros as follows: 

022 - 002 - 002-0 

or 

000 - 000-0000 
rather than - 

0000000000 

or 

0 - 0 - 0 - 0 - 0 - 0 - 0 - 0 - 0-0 

c. Adjust the microphone carefully, as 
demonstrated { see the picture). 

e. Leave a distinct pause between words. Ycu 

must wait for the green RIADY light to come 
cn before saying the next utterance. 

f. Use the proper volume. Watch the meter; 
the needle should be in the green area cr 
just slightly in the red on the peek parts 
of the word. Words trained in the lower 
white or upper red will give poorer results. 


121 



Cnee you are corfortaole with training the TeCC, I will 
ask you to operate the keyboard for the remainder of the 
training. I will remain nearby to provide assistance as 
required. Be sure to ask for help if you have any 
questions. Take breaks as you need them» a convenient place 
to break is every few pages. 

Operating the T600 ate 5*s sjs 5;s :^€ 5{c sis :{c 3;s sis 


To train a word - YOU TYPE 


T6O0 RESPONSE 


CTRL-U 

<word number> 
.e.g. 0 


WDi?: 

<word prorrpt> 
ZERO 


Now you say the word or phrase 10 times. Once the current 
phrase disappears you are ready to go onto the next word of 
the vocabulary. Again you type CTRL-U and continue as 
before . 


122 





APPENDIX D 
TYPING TEST 

TEE SOVIET NAVAL AIH FORCE 

FOR THE FIRST TII^F IN ITS HISTORY, THE SOVIET NAVAL 
AIR FORCE WILL BE PUTTING TO SEA WITH ITS OWN AIRCRAFT 
EMBARKED ON TEE FIRST OF TEE NSW SOVIET AIRCRAFT CARRIERS, 
THE KIEV, WHICH HAD ALREADY BEGUN ITS WORKING-UP TRIALS IN 
THE AUTUMN OF 1974. DISPLACING SOME 36,0^0 TONS WITH AN 
OVERALL LENGTH SLIGHTLY IN EXCESS OF 900 FEET, THE KIEV 
IS PRESUMED TO EMBARK 40-50 AIRCRAFT IN ALL, COMPRISING 
A MIX OF HELICOPTERS AND FIXED-WING V/STCL AIRCRAFT 
(TEE KIEV SHOWS NO SIGNS OF ARRESTER CABLES OR LAUNCH 
CATAPULTS). THE SUGGESTED VERSION OF THE STRIKE AND 
RECONNAISSANCE FIGHTER TO BE EMBARKED ON TEE KIEV IS TEE 
YAK-36, A VERSION OF WHICH WAS TESTED ON THE AIRFIELDS NEAR 
MOSCOW AND GIVEN SEA TRIALS ON THE SOVIET HELICOPTER- 
CARRIER MOSKVA. TEE YAK-36 UTILIZES VECTORED THRUST 
AND DIRECT LIFT IN COMiBINATION. SUCH AN AIR COMPLEMENT 
MIGET EE BROKEN DOWN INTO 30 KA-25 ASW HELICOPTERS AND 

15-20 V/STOL FIXED-WING AIRCRAFT. HOW MANY OF THESE 
CARRIERS WILL BE PRODUCED ? 

AT LEAST TWO OF THESE KIEV-CLASS AIRCRAFT CARRIERS ARE 
DUE TO ENTER SERVICE, WITH THE POSSIBILITY OF THE SOVIET 
NAVY PRODUCING A WHOLE CLASS OF SOME 6-e SHIPS, THEREBY 


123 



FACILITATING CCiNTINUCUS DFPLCYMENT OF ONE VESSEL IN BOTH THE 
^S^ITERRANEA^] ANL THE INLIAN OCEAN. TEE HELICOPTER 
COMPLEMENT PROVIDES INTENSIVE AS'.v CAPABILITY INTO DISTANT 
SEA AREAS (FOR DEFENSIVE AND OFFENSIVE PURPOSES), AS WELL AS 
FURNISHING AIRBORNE TARGET GUIDANCE FOR SURFACE-TO SURFACE 
ANTISHIP MISSLES. TEE V/STOL AIRCRAFT, WHILE PROVIDING A 
STRIKE CAPABILITY, MUST OBVIOUSLY INCREASE THE 
RECONNAISSANCE COVERAGE OF THE SOVIET NAVAL AIR ARM IN AREAS 
WHICH ARE BEYOND THE RANGE OF EXISTING LAND-BASED AIRCRAFT. 
MEANWHILE, THE ARMAMENT OF TEE KIEV-CLASS SHIPS IS ITSELF 
SIGNIFICANT. IT CONSISTS OF A TWIN LAUNCHER FOR ASW 
MISSLES, TWO 12-BARRELL MSU AS ROCKET LAUNCHERS, TWO SA-N-3 
SAM TWIN LAUNCHERS, A NUMBER OF RETRACTABLE SA-N-4 SAM 
LAUNCHERS, MULTIPLE 57-MM AAA MOUNTS AND SMALLER WEAPONS FOR 
CLOSE-IN PROTECTION AGAINST MISSLES AND OTHER GUIDED 
WEAPONS. 


124 


1 


i 

‘I 

I 

I 

I 

I 

i 

I 

i 

t 

i 


I 



APPENDIX E 


PP.S/POST SUBJECTIVE CUESTIONNAIRS 

Subjective Ciiesticnnaire Narre:_ 

INSTRUCTIONS; Express your feelira^^s regarding typed data 
entry and voice data entry. CIRCLE TEE NUN’BSR which BEST 
DESCRIBES your opinion for each question. 

1. Which data entry ncde do you think is the easiest to use 
to enter character strings and corrnands? 


Typed 

Data 

Entry 

<= <= <= 

Neutral 

_ V 

=> 

Voice 
Da ta 
Ent ry 
=> 

12 3 

4 


5 

7 

2. Which data entry 

fcr entering character 

mode do you 
strings and 

think is the 
commands? 

fas 

test mode 

Typed 

Data 

Entry 

<= <= <= 

Neutral 

* 

=> 

=> 

Voice 
Data 
Ent ry 
=> 

12 3 

4 

p; 

6 

7 

3. Which data entry 

character strings and 

mode is the 
conmands? 

mcst accurate 

fcr 

entering 

Typed 

Data 

Entry 

<= <= <= 

Neutral 

=> 

=> 

Voice 
Data 
Ent ry 
=> 

12 3 

4 

c; 

6 

7 


125 


























4. 'fthich data entry mode provides the most flexibilit 
general, for interaction with a computer? 


in 


Typed 



Neutral 



Voice 

Data 






Data 

Entry 






Entry 

< = 

<= 

< = 

* 

=> 

=> 

=> 

1 

2 

3 

4 

5 

6 

7 


£. «hich data 

several hours, if 

entry mode would you prefer 
required? 

to op 

erate for 

Typed 

Data 

Entry 

<= <= 

<= 

Neutral 

- => 

=> 

Voice 
Da ta 
Entry 
=> 

1 2 

*7 

4 5 

a 

w 

7 

6. 'A'hich data entry mode would you prefer 

more sporadic user of a computer system? 

to operate as a 

Typed 

Data 

Entry 

<= <= 

<= 

Neutral 

« => 

=> 

Voice 
Data 
Snt ry 
=> 

1 2 


4 £ 

6 

7 

7. Which data 

operation? 

entry 

mode promotes the 

most 

relaxed 

Typed 

Data 

Entry 

<= < = 

< = 

Neutral 

* => 

=> 

Voice 
Data 
Snt ry 
=> 

1 2 

3 

4 5 

6 

7 


126 














Which data entry rrode would be the irost advantageous to 


use to update 
information? 

an on* 

line data 

base of 

intelligenoe 

Typed 

Da t a 
Entry 
<= 

<= 

<= 

Neutral 

=> 

=> 

Voice 
Data 
Ent ry 
=> 

1 

2 


4 

5 

6 

7 

9. Which data 

interface in 

environment? 

entry mode provides the best man' 
a time-critical, high-pressure 

-me chine 
work 

Typed 

Data 

Entry 

<= 

<= 

<= 

Neutral 

=> 

=> 

Voice 

Data 

Entry 

=> 

1 

C 

3 

4 


6 

7 

10. Which data 

learn? 

entry 

mode do you 

think is 

the easiest to 

Typed 

Data 

Entry 

<= 

<= 

< = 

Neutral 

sit 

=> 

=> 

Voice 
Da ta 
Entry 
=> 

1 

2 

0 

4 

c; 

6 

7 


127 














APPENDIX F 


SUBJECT DATA SHEET 


Subject Data Sheet 


Date: 


Narr.e:_ Age; 

Service:_ PLank/Grade:_ 

Joh/Specialty Description (last job / next jcb) 


Prior to this experiment wnat has been ycur experience with 
voice data entry systems 7 Check one or more. 

_a. I have used a voice data entry system. 

_b. I have seen a voice data entry system demonstrated. 

_c. I have studied voice data entry systems (class, 

report, thesis, etc.) 

_d. I have no experience with voice data entry systems. 

If you checked a. above, circle the term that best describes 
your experience and skill with voice data entry. 

Experience - Skill- 

Considerable High 

(Moderate Average 

Minimal Novice 


Explain : 


If you checked c. above, please briefly state the extent 
of your studies. 


12S 

















I 


I 








AFPINDIX G 

INSTRUCTIONS BRIRFEr TO SUPJICTS 
TYPING f^CDI 

1. During this portion of the experir'ent you vill view 12 
cards and use the ADM terminal to write a report on each 
card similar to the one you saw in the sample (or other 
portion of the experiment). I will stop you after every 
four cards. This will give you a break end allow me to 
collect some data. 

2. You will be using a text editor at the ISII host 
computer. The edit keys discussed during training which may 
be used are shown on the carl at the terminal. You may edit 
errors only if you are on the line with the error in it, 
i.e. if you notice an error on the previous line, do not 
attempt tc correct it. However, I will demonstrate how you 
may void the previous line if you wish to do it over. 

3. Pencil and paper are provided if you want to use them to 
take notes as you look in the viewport. 

4. Now practice on this card. 

5. <critique the repcrt> 

6. Ycu are tc go as fast as you can while trying to 
minimize errors. Keep in mind you are writing an 
intelligence report which should be timely, accurate, and 
complete. Cuestions? 

7. Ck, start. 

6. <Trial rfl> 

9. Ok, stop. Rest a moment, then you will do four more. 

IZ. Ck, start. 

11. <Trial #2> 


129 














12. Ok, step. Rest a rrement , this is the last set cf feur 
you will type for the experiment. 

13. Ok, start. 

14. <.Trial ff3> 

15. Stop. You deserve a hreak. Relax a while. You may 
=^et up and move arcund, get a drink, etc. 


130 























V0ICS-UN3UFFSRED I^.ODE 

1. Luring this portion of the experiment you will view 12 
cards, ana use the T600 in unbuffered rrcde to write a report 
for each card like the one you saw in the sample (or other 
part of the experiment). I will stop you after every four 
cards. This will save you a break and allow me to collect 
some data. 

2. The Te03 unbuffered mode allows you to send the output 
corresponding to an utterance immediately to the host 
computer. So for example, when you say "CONFIRKID, ” it is 
sent immediately to the computer, and in this case, becomes 
a part of the text in tne text editor at the ISIS computer. 
You may edit your input as long as you are on the line that 
has the error using the edit commands you trained. A list 
of tne edit commands you use is provided for you here, along 
with a list of the vocabulary as reference material. 

5. If you look in the viewport at this time, you will see 
that the three bottom lines of tne 1600 display may be seen. 
These will provide a visual feedback of the text editor 
contents, and allow you to view the editing process as well 
as the carl. 

4. Now practice using the sample card provided. 

5. <critique the report> 

6. You are to go as fast as you can while trying to 
niinimize errors. Keep in mind you are writing an 
intelligence report which should be timely, accurate, and 
complete. Questions? 

7. Ck, start. 

6. <Trial #1> 

9. Ok, stop. Rest a moment, then you will do four more. 

10. Ok, start. 

11. <Trial #2> 


131 






12. C>, Stop. Rest a mc.'nent , this will be your last set of 

four to enter for the unbuffered rnode pert of the 
experindent. 

13 . Ck, start. 

14. <Trial #3> 

15. Stop. You deserve a break. Relax a while. You nay 
get up and move around, get a drink, etc. 


132 



vcics-BuriSRzr 


1. During this portion of the eiperirent you will view 12 
cards, and use tne T600 in buffered mode tc write a report 
for each card like the one you saw in the sample (or other 
part of the exper- iment). I will stop you after every four 
cards. This will ^ive you a break and allcw me to collect 
some data. 

2. The 1622 bufferea mode allows you to speak a chain of 
phrases prior to sending: them tc tne nest computer. Ycu ma^ 
edit the last utterance in the buffer by saying "kill line' 
cr its equivalent fer your vocabulary. If you make several 
errors, the entire buffer nay be erased with the command 
"kill line." Once you are ready to send the contents of the 
buffer, you say "go* or "carriage return," whichever you 
trained, and the character string will be sent tc the text 
editor at ISIS. However, you will not be able to use the 
editing features of the text editor at ISIS while in the 
buffered mode. I will demonstrate the buffered mode for ycu 
now . 


3. If you look in the viewport at this time, you will see 
that the three bottom lines of tne T600 display may be seen. 
These will provide a visual feedback of the buffer contents, 
and allow you to view the editing process as well as the 
card. 

4. Now practice using the sample carl provided. 

5. <critique the report> 

6. You are to go as fast as ycu can while trying to 
minimize errors. Seep in mind you are writing an 
intelligence report which should be timely, accurate, and 
complete. Questions? 

7. Ok, start. 

S. ^Trial ffl> 

9. Ck, stop. Rest a moment, then you will do four more. 

10. Ok, start. 

11. <Trial #2> 


133 


12. Ck, stop. Rest c rcrent, this l^ill be your Last set of 
four to enter for the buffered T’ode part of the ej.perinent. 

13. Ck, start. » 

14. <Trial ff3. 

15. Stop. You deserve a break. Relax a while. You may 
^et up and move around, get a drink, etc. 


134 




















APPEND IX H 


VOCABULAHY WORDS KISRECOGNIZED OR REJECTED 

NOTE: THE EOLLOWING LIST IS IN ASCENDING COLLATING SEOUENC 
BY UTTERANCE AND MISRECOGNITON . THE ISRECOGNI TI ONS HAV 
TEE FOLLOWING FORMAT: 

A (B) X N 


WHERE 


A = UTTERANCE ASSOCIATED WITH Te00 
MISRECOGNITION 

E = SPECIFIC TSee OUTPUT, IF DIFFERENT 
THAN A above; S.G.”(2)’’ MEANS 
THAT A NUMERAL WAS OUTPUT RATHER 
THAN THE WORD "TWO" 

N = NUMBER OF OCCURENCES 



s;: 5;s 5*,c 5^ s;: 3ic 3}: ^ 3^ sjc six >1? 

* UTTERANCE * 

* MISRECOGNITION(S ) - 

* :|e ^ :{s s^c sj: # # j*! sis s;£ 

31: 3^S 3;c 3 ( 1 : 5}C sjc 3|« 3;c 5jc sfc sjc 3}: 3;« 3{s s;« 3|« 3}C 5;« sic 3;s 3^ 

122-MM 

100-MM X 2 

12 2-MM 

152-MM X 3 

152-MM 

122-MM X S 

ee-MM. 

57-MM 

AA GUNS 

AN-8 CAMP X 6 

AA GUNS 

ANTI-TANK GUNS X 3 

AA GUNS 

YAK-2eP FIREBAR 

AIRCRAFT 

ANTI-TANK GUNS 

AIRCRAFT 

CARRIER 

AIRCRAFT 

TU-26 BACKFIRE 

AMPHIBIOUS 

FRIGATES X 3 

AM-e CAMP 

AA GUNS 

ANTI-TANK GUNS 

ANPHIBIOUS 

ANTI-TANK GUNS 

AN-6 CAMP X 4 

ANTI-TANK GUNS 

BEEP* X e 

ASSAULT GUNS 

BEEP* X 16 

ASSAULT GUNS 

MISSILE 

ASU-57 

AT-3 SAGGER 

AT-1 SNAPPER 

BEEP* 

AT-3 SAGGER 

APC 

BM-21 

M-44 

BM-24 

BM-21 

BMP-75PB 

BTR-6ePK 

BOATS 

BEEP* 


135 











•i*' v^ 

^ “r* n* ^ ^ 'c ^ ^ ^ n* 

- UTTZRANCZ - 


'T* *T* •T* 'it^ or 'i 


:}c ?;«5;c sis ;;s s;s >;: 5;c ;|s:{: s;? sjs >;« ^ >;t s*^ ?|s ^ ?;s 


»!= ^'ISRZCO&NITICN(S) - 

«/« S*-* vl^ «i« ayV 

O” or or -r or* ^ O' ^ ^ O' -T* "r o^ O'’ or ^ O' or ^r ^r o' ^r 


ROf^REPS 

30MBZRS 

BOMBERS 

BOMBERS 

BRAVO 

BRAVO CLASS 

BRAVO CLASS 

BRAVO CLASS 

ERDM 

BRBM 

ETR-152 

BTR-5e?K 

BTR-50PiC 

BTR-60PK 

CARRIAGE RETURN 

CARRIAGE RETURN 

CARRIAGE RETURN 

CARRIAGE RETURN 

CARRIAGE RETURN 

CARRIAGE RETURN 

CARRIAGE RETURN 

CARRIAGE RETURN 

CARRIAGE RETURN 

CARRIAGE RETURN 

CARRIAGE RETURN 

CARRIAGE RETURN 

CHARLIE I CLASS 

CHARLIE I CLASS 

CHARLIE I CLASS 

CONFIRMED 

CONFIRMED 

CONFIRMED 

CONFIRMED 

CONFIRMED 

CONFIRMED 

CONFIRMED 

CONFIRMED 

CONFIRMED 

CONFIRMED 

CONFIRMED 

CONFIRMED 

CONFIRMED 

CONFIRMED 

CONFIRMED 

CONFIRMED 

CONFIRMED 

CONFIRMED 


ALPHA (A) 

BEEP’:^ X 7 

IL-14 CRATE X 2 

LAUNCHERS 

FRIGATE 

GOLF I CLASS 

KOMAR CLASS X 2 

KOTLIN CLASS X 2 

TORPEDO 

YANKEE 

NINETEEN (19) 
BTR-6ePK X 4 
D-20 

BTR-50PE X 3 
AN-e CAM? X 4 
BEEP’!' X 2 
BRDM 

CARRIER X 11 
BRIGATE X 2 
FRIGATES 
HEAVY X 3 
SSN 

VICTOR (V) 

XRAY (X) 

YAK-2SP FIREBAR X 2 

ZSU-23/4 

FOXTROT CLASS 

KOTLIN CLASS 

MIRKA I CLASS X 2 

AIRBORNE 

BEEP* X 148 

BOMBERS 

BRAVO (B) X 4 

BRDM 

ELEVEN (11) X 6 
FIVE (5) X 7 
FOUR (4) 

HEAVY X 4 
KOTLIN CLASS 
LANDING 
LIMA (L) X 5 
MI-4 HOUND X 5 
MIKE (M) X 2 
NINE (9) 

NOVEMBER (N) X 2 
SA-6 GECKO 
SEVEN (7) X 2 


136 



%JL» hJU «A« 

'TT *1- O' O' 'i' ^r *¥• O' ^ O' 'I' 


- UTTERANCE * 

.J« *J« y« »u «V oA* 

'i' O' ^ O' O' O' ^ O' ^ ^ O' O' ^ 


V' *V V' 'A# W^ 'A' V*'' 'V 

O' ^ O' O' O' O' O' O^ ^ O' * 1 ' O' •'«' O' O' O' o'* O' ^ O' O' 


- MISRECCGN ITIGN(S ) * 

5;c5',cj;s5,*t3;i>;i>;s?{«?{?3;«5;c5{c5;??’^:Cc5;:5;<5(c5;«5^5ji5;? 


CCNEIRMED 

CONFIRMEE 

CONFIRMEE 

CONFIRMED 

CONFIRMEE 

CONFIRMEE 

CONFIRMED 

CONFIRMEE 

CONFIRMEE 

CRUISERS 

E-30 

D-44 

DASH 

EAS E 

DELETE LINE 

DELETE WORD 

DELETE WORE 

DELTA CLASS 

DELTA II CLASS 

ECHO I CLASS 

ECHO II CLASS 

ECHO II CLASS 

ECEC II CLASS 

EIGHT 

EIGHT 

EIGHT 

EIGHT 

EIGHT 

EIGHT 

EIGHT 

SIGHT 

EIGHT 

EIGHT 

EIGHT 

SIGHT 

EIGHT 

SIGHT 

ELEVEN 

ELEVEN 

ELEVEN 

ELEVEN 

ELEVEN 

ELEVEN 

ELEVEN 

ERASE 

FIELD GUNS 
FIELD GUNS 


TEN (le) 

TWELVE (12) X 7 
TWENTY (23) 
TWENTY-FIVE (25) 
TWENTY-ONE (21) 
UNIFORM (U) 

UPPER RIGHT 
XRAY (X) X 6 
Z SU-23/4 

TWENTY-THREE (23) 
D-74 

TWENTY-FOUR (24) 
QUEBEC (Q) 

TEN (10) 

LIMA (L) 

DELETE LINE (CTRL X) 
TWENTY-THREE (23) 
KOTLIN CLASS X 2 
GOLF II CLASS X 2 
PETYA I CLASS X 2 
DELTA II CLASS X 2 
PETYA II CLASS 
SEERSHEN CLASS 
AA GUNS X 4 
AMPHIBIOUS 
AN-8 CAMP X 3 
APC 

ASU-e5 
BEEP^ X 4 
EIGHTEEN (l8) X 4 
FIFTEEN (15) 

FOUR (4) X 5 
HEAVY X S 
KA-15 HEN X 14 
MEDIUM 
SA-S GECKO 
YANKEE (Y) X 7 
BEEP’*' X 6 
D-20 

FIVE (5) X 2 
FOUR (4) 

ONE (1) X 3 
UPPER LEFT 
UPPER RIGHT 
EIGHT (6) 

BEEP’!' X 2 
JULIETT X 2 


137 


ii: 




- UTTERANCE * 

*;!«Si: >J::(: # # :!s :{s 5j5 s;: sf: 


EIEIB GUNS 
EIEID HOWITZERS 
FIELD HOWITZERS 
FIELD HOWITZERS 
FIFTEEN 
FIFTEEN- 
FIGHTER 

FIGETER-EOf^BFRS 

FIGHTER-BOMBERS 

FIGHTER-BOMBERS 

FIVE 

FIVE 

FIVE 

FIVE 

FIVE 

FORTY 

FOUR 

FOUR 

FOUR 

FOUR 

FRIGATE 

FRIGATES 

FRIGATES 

FRIGATES 

FROG-3 

FROG-3 

FROG-4 

GO 

GO 

GO 

GO 

GO 

GO 

GO 

GOLF I CLASS 
GRISHA CLASS 
GRISHA CLASS 
GRISHA CLASS 
HEAVY 

HELICOPTERS 
HELICOPTERS 
HELICOPTERS 
HELICOPTERS 
HOTEL III CLASS 
IL-14 CRATE 
INSTALLATION 
INSTALLATION 


^ ^ ^ ^ sis 

* MISRECOGNITION(S) * 


5JC 5}S 3^6 sjs sis jjs :0c jjc J{s Sic 5{S si: Jjs 3ic ;$c5{« sjs Jjs ijc sjs 3{e 


T-IC 

BEEP’!' X 5 
HELICOPTERS X 4 
INTELLIGENCE 
EIGHTEEN (18) 
THIRTEEN (13) X 5 
FRIGATES 

ROCKET LAUNCHERS 
BEEP* X 3 
TWENTY-ONE (21) 
AN-e CAMP 
BEEP* X 2 
NINE (9) X 2 
PAPA (P) X 2 
QUEBEC (Q) X 2 
THREE (3) 

BEEP* X 33 
FROG-4 

LOWER RIGHT X 4 
MOBILE 
IL-38 MAY 
BEEP* 

FRIGATE 

SHSRSHEN CLASS 
BEEP* 

D-20 

PROBABLE 
BEEP* X 24 
BRAVO (B) X 2 
DELTA (D) 

ECHO (E) X 3 
GOLF (G) 

TWELVE (12) 

ZERO (0) 

OSA I CLASS 
KYNDA CLASS 
RIGA CLASS 
VICTOR CLASS 
SCUD B 
BEEP* X t 
BRAVO (B) 

FOXTROT (F) 

MI-4 HOUND 
HOTEL II CLASS X 3 
MI-24 HIND 
BEEP* X 3 
S-60 


138 


1 

i! 

I 

I 



3;c ^ ^ 

=<= UTTERANCE - 


INTELLIGENCE 
INTERCEPTORS 
INTERCEPTORS 
JULIET CLASS 
KA-16 HOG 
KANIN CLASS 
KANIN CLASS 
KANIN CLASS 
KANIN CLASS 
KANIN CLASS 
KANIN CLASS 
KARA CLASS 
KARA CLASS 
KARA CLASS 
KARA CLASS 
KARA CLASS 
KASHIN CLASS 
KASHIN CLASS 
KASHIN CLASS 
KASHIN CLASS 
KASHIN CLASS 
KASHIN CLASS 
KIEV CLASS 
KIEV CLASS 
KIEV CLASS 
KIEV CLASS 
KIEV CLASS 
KIEV CLASS 
KIEV CLASS 
KILL LINE 
KILL LINE 
KILL LINS 
KILL LINE 
KILL LINE 
KILL LINE 
KILL WORE 
KILL VCRD 
KILL WORD 
KILL WORD 
KOMAR CLASS 
KOMAR CLASS 
KOTLIN CLASS 
KOTLIN CLASS 
KOTLIN CLASS 
KOTLIN CLASS 
KOTLIN CLASS 
KOTLIN CLASS 


^ 3;::(e 

* MISRSCOGNITICN (S ) 

3;e 3;csj; Jje 3;c 3^ 3 ;: 3}: ;;c3;c 3ic :;c 


BEEP’:^ X 6 
BEEP* X 3 
HELICOPTERS X 6 
YURKA CLASS 
EIGHT (8) 

CARRIER 

KASHIN CLASS X 3 
KIEV CLASS 
KYNDA CLASS 
SHERSHEN CLASS X 4 
YANKEE CLASS X 5 
KANIN CLASS 
KOMAR CLASS 
KOTLIN CLASS X 3 
STENKA CLASS 
YURKA CLASS X 2 
JULIET CLASS X 8 
KANIN CLASS 
KOTLIN CLASS 
NATYA CLASS X 3 
SHERSHEN CLASS X 2 
YANKEE CLASS 
AIRCRAET 
JULIET CLASS 
KANIN CLASS 
KARA CLASS 
KYNDA CLASS X 2 
SHERSHEN CLASS 
STENKA CLASS X 6 
CHARLIE (C) X 6 
DELETE (CTRL X) 
KANIN CLASS X 2 
KOTLIN CLASS 
M-44 

MI-4 HOUND 
BEEP* X 6 
FIELD HOWITZERS 
KILL LINE X 2 
SEVEN t?) 

KARA CLASS X 2 
MIRKA I CLASS 
BRAVO CLASS 
CHARLIE II CLASS 
DELTA CLASS 
KASHIN CLASS 
KOMAR CLASS X 2 
MOSKVA CLASS 


139 




^:tc :{s sj?3;c Xs 

- UTTERANCE =*' 


si; j;« sj; 5{« ** 5S !(:❖>!«## Jr >}=# =<5 5r # 5r n!’!'>!« 

’i' MISRSCCGNITICN(S) - 




s;c 3 }: :{: >;c ^ Xc s|s 5j: s;s »;< 

KOTLIN 

CLASS 

POLNOCNY CLASS 

KOTLIN 

CLASS 

FOTI CLASS 

KOTLIN 

CLASS 

UPPER LEFT 

KRESTA 

I CLASS 

CHARLIE I CLASS 

KRESTA 

I CLASS 

ECHO I CLASS 

KRESTA 

I CLASS 

OSA I CLASS X 4 

KRESTA 

I CLASS 

RIGA CLASS 

KRESTA 

II CLASS 

NANUCKKA CLASS 

KRESTA 

II CLASS 

OSA II CLASS 

KRIVAK 

CLASS 

KANIN CLASS 

KRIVAK 

CLASS 

KARA CLASS X 2 

KRIVAK 

CLASS 

KOTLIN CLASS 

KRIVAK 

CLASS 

KYNDA CLASS 

KYNDA 

CLASS 

KANIN CLASS X 6 

KYNDA 

CLASS 

NATYA CLASS 

KYNDA 

CLASS 

RIGA CLASS 

KYNDA 1 

CLASS 

STENKA CLASS X 7 

LANDING 

BEEP* 


LAUNCHERS 

LIGHT 

LIGHT 

LIGHT 

LIGHT 

LIGHT- 

LIGHT 

LOWER LEFT 
LOWER LEFT 
LOWER LEFT 
LOWER LEFT 
LOWER LEFT 
LOWER LEFT 
LOWER LEFT 
LOWER LEFT 
LOWER LEFT 
LOWER LEFT 
LOWER RIGHT 
LOWER RIGHT 
LOWER RIGHT 
LOWER RIGHT 
LOWER RIGHT 
LOWER RIGHT 
LOWER RIGHT 
LOWER RIGHT 
M-1955 
1^-1955 
M-1955 
M-1976 


^;ORTARS X 6 
BEEP* X E 
FIVE (5) 

LOWER RIGHT X 2 
MIKE (N) X 4 
ONE (1) 

TWENTY (20) X 3 
BEEP=<' X 19 
BTR-50PK 
CORVETTES X 2 
KOTLIN CLASS 
LIGHT 

LOWER RIGHT X 9 
MOBILE X 3 
THREE (3) 
TWENTY-ONE (21) 
UPPER LEFT X 4 
BEEF* 

CONFIRMED 

LIGHT 

LOWER LEFT 
ONE (1) X 3 
SEVEN (7) 
SEVENTEEN (17) 
UPPER RIGHT X 8 
ASU-85 
BEEP* X 2 
SU-15 FLAGON 
PT-76 


140 



yu «v «v* ju Up ««« 


=5* UTTERANCE '■' 

«ju %>« mj^ aju y« yu u« yy u# yu yo u^ 

T n' •^•* V ^ <T‘ ^ ‘^■* -nr <Y* ^ ^ 


*•» %<* U« y« «•« Up »’p y« Up Up Up Up ..'p Up Up Up Up %»p %»p Up Up 

■T* n' nr ^r *’r nr >^r ^r ur n» nr n-* -n* n-* n» -nr nr n» n» ^r n» 


- r^ISRECOGNITION (S) - 

-T“ ^ ^ ^ ^ ^ -T* ^ n' •^r'r -"i*^ ^ ^ ^ 


h-242 
t^-4 EISOM 
^-4 BISON 
^"-4 BISON 
y'-44 
^-49 
r-49 
r^EDiur-’ 

M-ie HARKE 
MI-10 HARKE 
MI-12 HOMER 
MIG-19 FARMER 
MIG-21 FISHBED 
MIG-21 FISHBED 
MIG-23 FLOGGER 
MIG-2E FOXEAT 
MIG-2ER FOXBAT 
MIG-25R FOXBAT 
MIRKA I CLASS 
MIRKA I CLASS 
MRKA II CLASS 
MIRKA II CLASS 
MIRKA II CLASS 
MIRKA II CLASS 
MIRKA II CLASS 
MISSILE 
MOBILE 
MOBILE 
MOBILE 
MOBILE 
MORTARS 
MOSKVA CLASS 
MOSKVA CLASS 
MOSKVA CLASS 
MOSKVA CLASS 
NANUCHKA CLASS 
MANUCEKA CLASS 
NANUCHKA CLASS 
NANUCHKA CLASS 
NANUCHKA CLASS 
NANUCHKA CLASS 
NATYA CLASS 
NATYA CLASS 
NATYA CLASS 
NATYA CLASS 
NATYA CLASS 
NATYA CLASS 


EEEP’^ 

BEEP* 

CHARLIE I CLASS 
MI-6 HOOK 

TWENTY-FOUR (24) X 3 
M " 19 5 5 

TWENTY-FIVE (25) 
BEEP* 

1-11-24 HIND X 3 
MI-6 EIP 
MIG-19 FARMER 
RIGA CLASS 
IL-14 CRATE 
MIG-27 FLOGGER 
KA-25 HORMONE 
MIG-25R FOXBAT X 2 
KA-25 HORMONE 
MIG-25 FOXBAT X 3 
ECHO II CLASS 
PETYA I CLASS 
CHARLIE II CLASS X 2 
DELTA II CLASS 
KANIN CLASS 
KOTLIN CLASS X 2 
POLNOCNY CLASS 
TWELVE (12) 

BEEP- X 3 
BRAVO X 2 
HOTEL (H) 

PROBABLE X 6 
LAUNCHERS 
BEEP’!' X 2 
GOLF I CLASS X 3 
NATYA CLASS 
POLNOCNY CLASS X 5 
KOTLIN-SAM CLASS 
KYNDA CLASS 
SHERSHEN CLASS 
STENKA CLASS X 2 
YANKEE CLASS 
YURKA CLASS 
ALLIGATOR CLASS X 2 
BEEP’!' 

KANIN CLASS X 3 
KASHIN CLASS X 2 
KOTLIN CLASS 
KYNDA CLASS 


141 








^ 

#y» #|« ^ ^ ^ 'J' ?k» V ^ 

yu yu y^ y^ •JU •ju yu y^ y^ y# y# y^ 

>p #P rp ^p ^p ^1^ ^p ^p >p #p ^p #p 

- UTTiRANCI * 

* NISRSCCGNITION (S ) ’i-' 


Jjj sis j;; 5i: };£ J(s # ^ # j): j;: 5S !!< >!« jIs >;t 3i5sis 

KATYA CLASS 

POTI CLASS 

MNI 

BEEP* X 2 

MINI 

FIVE (5) X 5 

M N i 

LIGHT 

NINE 

MI-6 HIP 

NINE 

MIKE (M) 

NINE 

TWENTY (20) X e 

NINETEEN 

EIGHTEEN 

NINETEEN 

MIKE (M) 

NINETEEN 

THIRTEEN (13) 

ONE 

BEEP- X 4 

ONE 

FIVE (5) X 7 

ONE 

FOUR (4) 

ONE 

FOURTEEN (14) X 2 

ONE 

LIGHT X 2 

ONE 

M-44 

ONE 

UPPER RIGHT 

OSA I CLASS 

MIRKA I CLASS 

OSA II CLASS 

K,RESTA II CLASS X 2 

PETYA I CLASS 

NANUCHKA CLASS 

PETYA I CLASS 

YANKEE CLASS 

PETYA II CLASS 

ECHO II CLASS 

PETYA II CLASS 

HOTEL II CLASS 

PETYA II CLASS 

KASHIN CLASS 

PETYA II CLASS 

SEERSHEN CLASS 

POLNOCNY CLASS 

ALLIGATOR CLASS 

POLNOCNY CLASS 

BSEP’i' X 2 

POLNOCNY CLASS 

ECHO II CLASS 

POLNOCNY CLASS 

HOTEL II CLASS 

POLNOCNY CLASS 

HOTEL III CLASS 

POLNOCNY CLASS 

KOTLIN CLASS 

POLNOCNY CLASS 

MOSKVA CLASS 

POSSIBLE 

BEEP* 

POTI CLASS 

KANIN CLASS 

POTI CLASS 

KOTLIN CLASS X 3 

POTI CLASS 

MOSKVA CLASS X 6 

POTI CLASS 

ROMEO CLASS 

POTI CLASS 

WHISKEY CLASS X 2 

FRIMORYE CLASS 

ECHO I CLASS 

PRIMORYE CLASS 

MIRKA I CLASS 

PRINORYE CLASS 

MIRKA II CLASS 

PROBABLE 

BEEP* 

PROBABLE 

FRAVO (B) X 7 

PROBABLE 

MOBILE X 3 

PROBABLE 

POSSIBLE 

PROBABLE 

TORPEDO 

PROBALBLS 

TWENTY-FOUR (24) 


142 


I 


I 




n' ^ ^ 5j5 SjS >}l 3{C ^ Jjt 5{i 3{i 

%<« V-' 

-1^ ^ ^ ^ n' nr ^ V V n'* ^ -Y* •'r n^ V nr ^r 

UTTERANCE 

- MISRECOGNITICN(S) * 


?;« Sli 5;x :*s :Js ?j! 5}: ^ 5j: 5{C 5^5 3;s >;c 5tc>;s 5j! Jjc 5;c 

RECONNAISSANCE 

SEEP- X 4 

RECONNAISSANCE 

CRUISERS 

RECONNAISSANCE 

GRISHA CLASS 

RECONNAISSANCE 

INTELLIGENCE X 2 

REPEAT LINS 

CARRIAGE RETURN (CTRL M) 

REPEAT LINE 

D-20 

REPEAT LINE 

M-240 

REPEAT LINS 

THREE (3) 

RETURN 

BEEF’S^ X 4 

RETURN 

CONFIRMED X 5 

RETURN 

ELEVEN (li; 

RETURN 

SEVEN (7) X 2 

RETURN 

TEN (10) X 2 

RIGA CLASS 

GRISHA CLASS X 5 

RIGA CLASS 

VICTOR CLASS X 3 

ROMEO CLASS 

POLNOCNY CLASS 

S-60 

SS-16 

S-60 

SSG X 2 

SEVEN 

ASSAULT GUNS 

SEVEN 

BEEP* X 3 

SEVEN 

ELEVEN 

SEVEN 

FIVE (5) 

SEVEN 

SCUD A X 11 

SEVEN 

SEVENTEEN (17) 

SEVEN 

SIERA (S) X 2 

SEVEN 

WHISKEY CLASS 

SEVEN 

ZSU-57/2 

SEVENTEEN 

SCUD A X 3 

SEERS ESN CLASS 

KANIN CLASS X 4 

SHIPS 

SIX (6) X 2 

SIX 

BEEP* 

SIX 

DESTROYERS X 3 

SIX 

FRIGATES 

SIX 

INDIA (I) 

SIX 

SCUD B 

SIX 

SHIPS X 9 

SIX 

SPACE ( ) X 20 

SIX 

T-72 

SIXTEEN 

BEEP* 

SIXTEEN 

FIFTEEN (15) X 4 

SPACE 

AMPHIBIOUS X3 

SPACE 

BACKSPACE (CTRL A) 

SPACE 

FRIGATES X 2 

SPACE 

SHIPS 

SPACE 

T-10 

SS 

SSGN 

SS 

SSM 


143 


J 


4 

{ 




j;: ^*5 >;s sis :js 

UlTIRANCI 

%f* V.» %l^ »•* V'' 

'j- *1' -T* •r* 'n 'r- "T* 'i» ^ *r» ^ 

- N-ISRECCGNITION ( S ) - 

***^ Vi* V* ^'* 

*r» ^ Of* *1 *i»' ^ *T* ^-v ^ ^ ^ ^ ^ *1^ *f* 

SS-14 SCAPIGOAT 
SS-C0 

SS2 

SSSN 

SSBK 

SSG 

SSG 

SSGN 

SSGN 

SSGN 

SSGN 

SSGN 

SSH 

SSN 

SS N 

STiNKA CLASS 

ST2NKA CLASS 

STENKA CLASS 

STENKA CLASS 

STENKA CLASS 

STENKA CLASS 
STRIKE/ATTACK 
STRIKE/ATTACK 
STHIKE/ATTACK 

SU-15 FLAGON 

SU-19 FENCER 

SU-A9 FISHPOT 
SVERDLOV 

SVERDLOV CLASS 
SVERDLOV CLASS 
SVERDLOV CLASS 
SVERDLOV CLASS 
T-34/65 

T-34/S5 

T-34/B5 

T-34/e5 

T-34/B5 

T-54/B5 

T-54/55 

T-54/55 

T-54/55 

T-62 

TANGO 

TANGO CLASS 

TANKS 

TANKS 

TANKS 

SA-6 GECKO X 3 

SSF 

SSG X 6 

SSB X 5 

SSGN X 10 

SSE X 2 

SSGN 

CHARLIE I CLASS 

SS3N X 31 

SSG 

SSM 

SSN X 4 

SA-6 GAINFUL 

SSN X 20 

SSiN 

JULIET CLASS 

KANIN CLASS 

KYNDA CLASS 

NATYA CLASS X 2 
SEERSHEN CLASS 

VICTOR CLASS X 2 

AN-6 CAN’P 

BEEP’^' X 2 

M-1955 

IL-36 MAY 

SS-16 

BEEP* 

BEEP* 

OSA I CLASS X 2 
POLNOCNY CLASS 

STENKA CLASS X 2 

YURKA II CLASS 

ASU-85 

M-1955 X 2 

MIG-21 EISE3ED 

T-54/55 

TU-26 BACKFIRE X 3 
BEEP* X 2 

BMP-76PB 

I)-44 

T-34/S5 X 20 

TU-16 BADGER 

NINE (9) 

NATYA CLASS 

BEEP* 

BEEP* X 2 

HEAVY 


144 



- UTTERANCE - 

4^ #1^ rp #1% 

^ .^ISRSCCGMTION (S ) * 

j;< ?;€};« 55e 5;c»;«sjc 5;s;Jc :;s5ls s;? 5)5 3;? :Jc ?;? 

TANKS 

TANKS 

TEN 

TEN 

THIRTEEN 

THREE 

THREE 

THREE 

THREE 

THREE 

THREE 

THREE 

THREE 

THREE 

TEHEE 

TU-22 BLINDER 

TU-28 BEAGLE 

TU-28P FIDDLER 
TWELVE 

TWELVE 

TWENTY 

TWENTY 

TWENTY 

TWENTY 

TWENTY 

TWENTY 

TWENTY 

TWENTY 

TWENTY-FOUR 

TWENTY-ONE 

TWENTY-ONE 

TWENTY-THREE 

TWENTY-TWO 

LOWER LEFT 
TWENTY-TWO 

TWO 

TWO 

TWO 

TWO 

TWO 

TWO 

TWO 

TWO 

TWO 

TWO 

TWO 

TWO 

NINETEEN (19) 

TWENTY (20) 

BEEP’>= 

ELEVEN (11) 
jilFTEEN (15) 

CARRIER 

FOURTEEN (14) X 2 
FRIGATE X 8 

F ROG-3 

HEAVY X 2 

Ml-e HIP 

THIRTEEN (13) 

TWENTY (20) 

TWO (2) 

WHISKEY (W) 

TU-2e BEAR 

IL-14 CRATE X 2 
hIG-23 FLOGGER 

GOLF 

BEEP’!' X 4 

D-30 

FOURTEEN (14) 

LIGHT 
^^IKE (N-) 

NINETEEN (19) 

ONE (1) 

UPPER RIGHT 

TWENTY-ONE (2l) 

mirTP3^« Y 

TWENTY-FOUR (24) X 2 
FROG-3 

BEEP’*' X 2 

LOWER RIGHT X 9 
TWENTY-THREE 

BEEP- X 12 

BTR-152 

EIGHT (8) 

FIFTEEN (15) 

FOUR (4) X 2 

FRIGATE 

HEAVY 

LIGHT 

MEDIUM X 4 

T-10 

T-e2 

T-72 


145 



^ ^ y<* 

#1% #1% #*y^ r|% 

* UTTIRANCE - 

A ils il2 3ic iJs sdc 2lr 5*r i!r ^£ i!t 2i a!s 


TWO 

TWO 

TWO 

TWO 

TWO 

TWO 

TWO 

UNIFORM 
UPPZR LEFT 
UPPER LEFT 
UPPER LEFT 
UPPER LEFT 
UPPER LEFT 
UPPER LEFT 
UPPER LEFT 
UPPER RIGHT 
UPPER RIGHT 
UPPZR RIGHT 
UPPZR RIGHT 
UPPER RIGHT 
VICTOR 
VICTOR 
VICTOR 
VICTOR 
VICTOR 
VICTOR 
VICTOR 
VICTOR 
VICTOR 
VICTOR 
VICTOR 
VICTOR 
VICTOR 
VICTOR 
VICTOR 

VICTOR CLASS 
VICTOR CLASS 
VICTOR CLASS 
VICTOR CLASS 
VICTOR CLASS 
WHISKEY CLASS 
YAK-26P FIREBAR 
YAK-26P FIREBAR 
YANKEE CLASS 
YURKA CLASS 
YURKA CLASS 
YURKA CLASS 


y^ y* y^ y^ sy y^ yy y^ 

# 1 ^ > 1 % > 1 ^ #|« < 1 ^ ^ 1 % ^ 1 % 


MISRSCCGNITION (S) 

:;5 3;^ jlc 5;< 5;: 5{c 5{; sjt 3^ 5^ 5|c 5;c 


TEN (le) X 4 
TERES ^3) X 6 
TU-22 BLINDER 
TWENTY-TWO (22) X 5 
YAK-26P FIREBAR 
2SU-57/2 X 12 
ZU-23/2 X 8 
BRDM 

BEEP* X 21 
BRAVO CLASS X 3 
EIGHTEEN (18) 

ELEVEN (11) 

KOTLIN CLASS X 3 
LOWER LEFT X 5 
UPPER RIGHT X £ 
BEEP’!' X 8 
LIGHT 

LOWER LEFT X 4 
LOWER RIGHT X 9 
UPPER LEFT X 7 
BEEP’S' X 17 
CARRIAGE RETURN 
CARRIER X 2 
D-30 

FIFTEEN (15) X 2 
FRIGATE X 2 
HEAVY 

INDIA (I) X 2 
M-1955 

NOVEMBER (N) 

QUEBEC (Q) X 2 
SA-6 GECKO 
THREE (3) X 2 
TU-2e BEAR 
WHISKEY 
BEEP’S* 

KARA CLASS 
KYNDA CLASS X 2 
MIRKA II CLASS 
NANUCHKA CLASS 
KANIN CLASS 
MIG-19 FARMER 
TU-28P FIDDLER 
KANIN CLASS X 4 
KYNDA CLASS 
PRIMORYF CLASS 
VICTOR CLASS X 3 


146 


^ 

* UTTERANCE ^ 

^ ^ ju ^ ^ 

0\^ ^1% r,% #1% 

5;c:;:s;c^:^j;c5;:5jc^3{s3;c3t:5lc5;2 5;s;;c:;cs5t:;cs;c:;:^ 

- MSRSCOGMTION (S) 

O'** V* ^V 

#1% ^|4 #1% #1^ ^1% #1% #1% 

ZERO 

ZERO 

ZERO 

ZERO 

ZSU-23/4 

ZSU-57/2 

ZSU-57/2 

ZSU-57/2 

ZU-23/2 

ZU-23/2 

ZU-23/2 

backspace (CTRL A) 

KILO (K) X 2 
hOBILE 

ZSU-57/2 X 2 

ZU-23/2 X 2 

ASU-57 

ZSU-23/4 

ZU-23/2 

SU-19 FENCER 

TU-22 BLINDER 

TU-26 BACKFIRE 


147 


APPENDIX I 


RESULTS FOR PRE/POST SUBJECTIVE QUESTIONNAIRE 

The followine,' data reflect whether subjects' attitudes 
shifted either toward typing or voice as a result cf the 
experiment. A two-tailed si^^ test was used. Note: Means 
for the pre/post given below may be misleading if thought to 
be indicative of the shift. Tne sign test looks at the fact 
of whether their was a shift or not, and ignores the amount 
of shift in the analysis, since the amount may be somewhat 
arbitrary. 


QUESTIONS and 

PRS / POST MEANS 
for 20 subjects. 

SHIFTS 
towa rd 
TYPING 

SHIFTS 
towa rd 
VOICE 

NO 

SHIFT 

OC =.10 

S ignif? 

1. Which data entry m.ode 
do you think is the 
easiest to use to enter 
character strings and 
commands? (5.1/6.1] 

T 

12 

p 

YES 

2. Which data entry mode 
do ycu think is the 
fastest mode for entering 
character strings and 
commands? (5.1/5.6) 

3 

13 

4 

YES 

3. Which data entry mode 
is the most accurate for 
entering character 
strings and commands? 

(4.1/4.8) 

4 

9 

7 

NO 

4. Which data entry mode 
provides the most 
flexibility, in general, 
for interaction with a 
computer? (5.1/5.1) 

4 

12 

4 

YES 

5. Which data entry mode 

3 

8 

9 

NO 


would you prefer tc 
operate for several 
hours, if required? 

(4.3/4.3) 


146 




I 


i 


Id 

I 

I 


I 


CUESTIONS and 
PRI / POST r.EANS 
for 2i2 subjects. 


SHIFTS SHIFTS 
toward toward NO 
TYPING VOICE SHIFT 


6. Which data entry rrode 
would you prefer to 
operate as a more 
sporadic user of a 
computer system? 

(4.2/4.3) 


7. Which data entry mode 
promotes the most relaxed 
operation? (5.0,5.1) 

6. Which data entry mode 
would be the most 
advantageous to use to 
update an on-line data 
base of intelligence 
information? (5.1/5.0) 

9. Which data entry mode 
provides the best 
man-machine interface in 
a time-critical, high 
pressure work 
environment? (5.0/5.0) 

10. Which data entry 
mode do you think is the 
easiest to to learn? 

(4.9/5.6) 


3 10 7 


5 6 7 

3 9 6 


1 =, 


12 


2 13 5 




OC =.10 
Signif? 


YES 


NO 


NO 


NO 


YES 


149 




1 




0 





ft 




LIST OF REIERENCiS 


1. Lea, W. A., Treads in Speech Recogaitioa . Prentice-Hall 

Inc., p. 68-c9, I960. 

2. Naval Postgraduate School Report NPS-55-60-016, 

Experiments with Voice Input for CoriTiand and Control , 

hy G.K.Poock, April 1960. 

3. Lawson,S., "Naval Tactical C3 Architecture 1985- 

1995," Signal, p. 72-76, August 1976. 

4. Lea, op. cit., p. 3. 

5. Rome Air Development Center Briefing, "dOD Automated 

Exploitation System," February 1961. 


6 . 

Ibid 

• 



7. 

Lea, 

op. cit.. 

P. 

30-3 

6 . 

Lea, 

op. cit., 

? • 

40. 

9. 

Lea, 

op. cit.. 

P • 

24. 

10 . 

Lea, 

op. cit., 

P- 

92. 

11. 

Lea , 

op. cit.. 

P- 

4-7. 


12. Peek, B., Meuberg, E.P. and Eodge, D.C., 'An Assessment 

of the Technology of Automatic Speech Recognition for 
Military Applications," IEEE Transactions Acoustics, 
Speech, and Signal Processing, ASSP-25, Number 4, p. 
310-322, 1977. 

13. Rome Air Development Center Report RADC-TR-80-220, DIMS 

Voice Data Entry , by Phillips E. Scott, Threshold 
Technology Inc., June 1980. 

14. Rome Air Development Center Report RADC-TR-7S-209, Word 

Recognition . by Phillips B. Scott, Threshold 
Technology Inc., September 1976. 


15 ? 










15. Potre Air Devsloprrect Center Report RADC-TH-77-164, 
Alpha/Numeric Sxtraction Techr.lQiie Phase II . by 

Phillips B. Scott, Threshold Technolot^y Inc., Key 

1977. 

16 . Foock, op. loc. 

17. KcSorley, W., Using Voice Kecoignition to Run the Warfare 
Environment Simulator Masters Thesis , Naval 

Postgraduate School, Monterey, California, March 1961. 

IS. Rome Air Development Center Report RADC-TR-80-74, 
Advanced Image Exploitation Aids , by John R. Welch 
and E. Shamsi, March 1950. 

19. Pccck, op. Icc. 

20. Threshold 600 User's Manual, Threshold Technology Inc., 

1978. 

21. Conners, E., and Vance C., "Operation of tne ^0-1130 

Harvard Tachistoscope and Peripheral Equipment," Navel 
Postgraduate School CS 3565 Paper, p. 1-3, September 
1978. 

22. United States Strategic Institute Report, USSI 76-2, 

Soviet Warsaw Pact Force levels , by J. Erickson, 1976. 

23. Donnely, C., and others. The Soviet War Machine; An 

Encyclopedia of Russian Military Equipment and 

Strategy , Chartwell Becks, Inc. 1976. 

24. Defense Intelligence Agency DBB-2680-40-78, Handbook on 

the Soviet Armed Forces . February 1976. 

25. Wiener, E., The Armies of the Warsaw Pact Nations . 2nd 

ed., Carl Ueberreuter Publishers, 1978. 


151 















INITIAL DISTF.IEUTICN LIST 


No. 


1. Defense Technical Information Center 
Cameron Station 

Alexandria, Virginia 22134 

2. Superintendent 

ATTN: Litrary, Cede 0142 
Naval Postgraduate School 
Monterey, California 93940 

3. Superintendent 

ATTN: Department Chairman, Code 55 
Naval Postgraduate School 
Monterey, California 93940 

4. Superintendent 

ATTN: Professor J. Arima, Code 55Aa 
Naval Postgraduate School 
Monterey, California 93940 

5. Superintendent 

ATTN: Professor R. Sister, Code 55Sa 
Naval Postgraduate School 
Monterey, California 93940 

5. Superintendent 

ATTN: CDR W. Moreney, USN, Code 55Mp 
Naval Postgraduate School 
Monterey, California 93940 

7. Superintendent 

ATTN: Professor D. Neil, Code 55Ni 
Naval Postgraduate School 
Monterey, California 93940 

6. Superintendent 

ATTN: Professor G. PcccR, Code 55Pk 
Naval Postgraduate School 
Monterey, California 93940 

9. Superintendent 
ATTN: Code 312A 
Naval Postgraduate School 
Monterey, California 93940 


C cpies 
2 

2 

1 

1 

1 

1 

1 

10 


152 




10. Superintendent 1 

ATTN; Cede 39 

Naval Postgraduate School 
^’onterey, California 93940 

11. Air Force Institute of TecnncIcgy/CIS? 1 

ATTN: Major Charles Farnhart, USAF 

Wright Patterson Air Force Base 
Ohio 45433 

12. Air Force Intelligence Service/INT 2 

ATTN: It Ccl W. Cray, USAF 

Bolling AFB, Washington, D.C. 20332 

13. Rorre Air Development Center/IRE 2 

ATTN: E. Benfeld, IDES 

Driffiss AFB, New York 13441 


13. Rome Air Development Center/IRRA 2 

ATTN: Lt J. Woodard 

Criffiss AFB, New York 13441 

14. Aeronautical Systems Division/RWT 1 

ATTN: Lt Col J. Turinetti 

Tactical Reconnaissance Projects 
Wright Patterson AFB, Ohio 45433 

15. Strategic Air Command/INXY 2 

ATTN: Capt Greg Jay, USAF 

Offutt AFB, Nebraska 6ftll3 

16. American Sterilizer Company 1 

ATTN: T. Brendgord 

2424 West 23rd St 
Erie, Pennsylvania 16152 

17. Crew Systems Technology 1 


ATTN: Donald L. Parks 
Seeing Commercial Airplane Co. 

P.O. Box 3707 
MS 47-08 

Seattle, Washington, 98124 

IS. Dipl.-ing Eartmut Mutschler 1 

Wissencraftl.Mitarbeiter 
Fraunhofer-Institute Fur 
Informations-Und Da tenverabelting 
Rintheimer Strabe 19 
D-7500 Karlsruhe 1 
Germany 


153 














1 


19. SeneraL Dynarrics 
ATTN: J. Mke Byrd 
hail Zone 8227-1 
P.O. Box S5106 
San Diego, California 92136 

20. Babcox and Wilcox 1 

Nuclear Power Generation Division 

ATTN: Robert L. Starkey 
P.O. Box 1260 
Lynchburg, Virginia 24505 

21. International Telephone and Telegraph 1 

Great Pasters House 

Human Factors 
ATTN: Barry Drake 
Edinburgh Way 
Harlow, Essex 
England 

22. Texas Instruments, Inc. 1 

Human Factors 

ATTN: Kenneth C. Bice 
P.O. Box 2909 
MS 2201 

Austin, Texas 76763 

23. Walt Goede 1 

Consultant 

31051 Hawksmoor Drive 

Rancho Palos Verdes, California 90274 

24. International Telephone and Telegraph 1 

ATTN: H. Rudy Ramsey 

1000 Oronoque Lane 
Stratford, Connecticut 06497 

25. Lear Siegler, Inc 1 

ATTN : Ivan Belya 

4141 Eastern Avenue S. E. 
hS 128 

Grand Rapids, Michigan 49506 

26. TRW 1 

MTS-Men-Machine Interface 

System Design Department 
ATTN: C. E. (NED) Wilkins 
Cne Space Park 

Redondo Beach, California 90278 


154 



27 . 


1 


TRW 

Systems Analysis Eepartment 
ATTN: (Matthew F. Carroll 
MS 75-190 
One Space Park 

Redonio Beach, California 9027S 

26. American Telephone and Telegraph 1 

ATTN : R . E. Cochrane 

Engineering Maniger for Human Factors 
Room 4C154 

Eelminster, New Jersey 07921 

29. general Motors Corporation 1 

Industrial Relations Staff 

Director-Ergonomics 
Health Services 
ATTN: Roger L. Kuhn 
3044 West Grand Elvd. 

Detroit, Michigan 46202 

30. Northrop Corporation 1 

ATTN; Jeffrey E. Miller 

2301 West 120th Street 
Eawthorne, California 90250 

31. Northrop Corporation 1 

Electronics Division 

ATTN: Compass Preview Program Manager 
1 Research Park 

Palos Verdes Peninsula, California 90274 

32. John Herchenroder 1 

204 North Wakefield Street 

Arlington, Virginia, 22203 

33. Sperry Univac 1 

ATTN: Michael L. Schneider 

Computer Scientist 
P.O. Box 500 

Blue Bell, Pennsylvannia 19424 

34. U.S. Army Human Engineering Lab 1 

ATTN: Richard N. Armstrong 

Box 476 

Fort Rucker, Alabama, 35362 


15 ^ 



Ohio State University 


1 


Industrial and Systems J!.ngineerin? 


ATTN: Gayle L. Berry 
1971 Neil Avenue 


Columbus, Ohio 43210 


26 . 


University of Nebraska at Lincoln 


1 


Industrial Engineering 
ATTN: David J. Cochran 
Lincoln, Nebraska 65586 


37. Systems Research laboratories 
Human Factors Engineering 
ATTN: Chris Hale 
2600 Indian Ripple Road 
Dayton, Ohio 45440 


1 


38. University of California 


1 


Computer Science and Applied Math Department 

Lawrence Berkeley Lab 

ATTN: Aaron Marcus 

Building 503 

Room 2238 

Berkeley, California 94720 

39. Bunker Ramo 1 

Electronic Systems Division 

ATTN: CATIS Program Manager 
31717 La Tienda Drive 
Box 5009 

Westlake Village, California 91359 

40. Texas Instruments, Inc. 1 

Electronic Systems Division 

ATTN: TIPI Program Manager 
Lewisville, Texas 75067 

41. Harris Corporation 1 

ATTN: Larry Lamb 

MS 22/2419 
P.O. Box 37 

Melbourne, Florida 32901 

42. Rodney Elden 1 

Management Consultant 

5 Middle Road 

Broniville, New York 10708 


156 



43. Defence and Civil Institute of 1 

Invironmental i^edicine 

ATTN: Ing. L. Van Breda 
P.O. Box 2002 
1133 Sheppard Avenue West 
Downsview, Ontario 
Canada MM 3B9 

44. Naval Ocean Systerrs Center 1 

ATTN: Carl Rcsengrant, Code 6141 

San Diego, California 92152 

45. Merck and Corrpany 1 

ATTN: Nancy Woo 

R 84-17 
Box 2000 

Rahway, New Jersey 27065 

4c. National Aeronautics and Space Administration 1 

ATTN: 2. L. Weiner 
MS 23903 

Moffett Field, California 94035 

47. Naval Undersea Systems Center 1 

ATTN: Anthony Bessacini, Code 3522 

Newport, Rhode Island 02S42 

48. National Security Agencey 1 

ATTN: John F. Boehm 

R542 

Fort Meade, Maryland 20750 

49. Naval Training and Equipment Center 1 

ATTN: R. Breaux, Code M-711 

Orlando, Florida 32613 

50. Office of the Undersecretary of Defense 1 

Research and Engineering 

ATTN: Cdr Paul Chatelier, USN 
Room 3D129 

Pentagon, Washington, D.C. 20301 

51. National Aeronautics and Space Administration 1 

ATTN : Clay Coler 

MS 23902 

Moffett Field, California 94235 


157 


I 








52. t\dval Undersea Systems Center 1 

ATTN: Dianne Davis, Cede 3522 

Newport, Rhode Island 

53. Naval Undersea Systems Center 1 

ATTN: Idward De Gregario, Code 3522 

Newport, Rhode Island 22340 

54. U.S. Army Engineer Topographic and 1 

and Research Institute 

ATTN : Tice De Yeung 

Fort Eelvoir, Virginia 22060 

55. U.S. Army Applied Technology Lab 1 

Fort Sustis, Virginia 23662 

56. United States Postal Service 1 

Research and Develcnment Lab 

ATTN : Harold C. Glass 
11711 Parklawn Drive 
Rockville, Maryland 20852 

57. Air Force Aerospace Medical Research lab 1 

ATTN; Don Me Kechnie 

Wright Patterson AFB, Chio 45433 

58. Air Force Aerospace Medical Research Lab/EEA 1 

ATTN: Thomas J. Moore 

Wright Patterson AFB, Ohio 45433 

56. Air Force Aerospace Medical Research Lat/EBM 1 

ATTN; Capt Vince Mortimer, USAF 
Wright Patterson AFB, Ohio 45433 

59. Naval Aerospace Medical Research Lab 1 

Acoustical Sciences Division 

ATTN; James Mesko 
Naval Air Station 
Pensacola, Florida 52506 

60. U.S. Army Signal Center 1 

Directorate of Training 

ATTN: Capt Leslie Scofield, USA 
Fort Forden, Georgia 30905 

61. Naval Air Development Center 1 

ATTN; C. Skriver, Code 6021 

Warminster, Pennsylvania 13974 


156 





m 





62 . i\aval Undersea S/star's Center 
ATTN: S. Nils Straaveit, Code 317 
New London, Coaneoticnt 26322 

63 . Fleet Material Support Office 
ATTN: Leahrrond Tyre, Code 9333 
Mechanicsturg , Pennsylvania 17C55 

64. Air Force Weapons Analysis Laboratory/FGR 
ATTN: Eric Werkowitz 

Wrieht Patterson AF3, Chio 45433 

c5. Naval Air Development Center 
ATTN: T. Weiner, Code 4043 
Warminster, Pennsylvania 16974 

66 . Naval Air Systems Command 

ATTN: Cdr Chuck: Hutcnins , Air-340F 
Jefferson Davis Highway 
Arlington, Virginia 20360 

57. Army Communicative Technology Office 
ATTN: Major W. MacHarrie 
Box 4337 

Fort Sustis, Virginia 23624 

cS. National Securtity Agency 
ATTN: Charles Wayne 
.R54 

Fort Meade, Maryland 20755 

69. DAVAA-S 

Avionics Research and Development 

ATTN: Lockwood Reed 

Fort Monmouth, New Jersey 07703 

70. Army Research Institute 
PERI-0U 

ATTN: J. N. McConnell 
5001 Eisenhower Avenue 
Alexandria, Virginia 22333 

71. Air Force Aerospace Medical Research Lab/BBA 
ATTN: P.ichard McKinley 

Wright Patterson AFB, Chio 45435 


1 

1 

1 

1 

1 

1 

1 

1 

■1 

± 

1 



72. Texas Instruments, Inc. 

ATTN: George roddinglon 
Eox 225956 

MS 371 

Dallas, Texas 75243 

73. IBM Research Center 
ATTN: N. Hex Dixon 
Box 2lS 

Yorktown Heights, New York 10596 

74. Massachusetts Institute cf Technology 
ATTN : Victor Zue 

Room 36-543 

Camhridge, Massachusetts 02139 

75. Bolt, Beranek, and Newman, Inc. 

ATTN: Jared Wclf 

50 Moulton Street 

Camhridge, Massachusetts 02238 

76. Naval Air Development Center 
ATTN; Norm Warner, Code 6021 
Warminster, Pennsylvania 18974 

77. Robert Lynchard 
3165 McCrory Place 
Orlando, Forida 32603 

78. Naval Aerospace Medical Research Lab 
ATTN: Cdr James Goodson 

Naval Air Station 
Pensacola, Florida 32508 

79. Armament Division/XRC 
ATTN; H. F. Brown 
Fglin AF3, Florida 32541 

80. Naval Aerospace Medical Research Lab 
Acoustical Sciences 

ATTN; Carl Williams 
Naval Air Station 
Pensacola, Florida 52508 

81. Naval Air Test Center 

Systems Engineering Test Directorate 
ATTN: Andrew Cruce, Code 57030 
Patuxent River, Maryland 20670 


1 

1 

1 

1 

1 

1 

1 

1 

1 

1 


160 




62. Internal Revenue Service 1 

ATTN; Thcn^as Cullen 
1201 East Street NW 
■A'ashingtcn, D.C. 20224 

£3. Internal Revenue Service 1 

ATTN: Xlaus Erosius 
1201 East Street NW 
Washington, E.C. 20224 

54. Vertex Corporation 1 

ATTN: Janet Baicer 
Two Oak Park 

Bedford, [Massachusetts 01730 

65. United States Postal Service 1 

Research and Development Lab 
ATTN; Arnold Craft 
11711 Parklawn Drive 
Rockville, Maryland 20852 


£6. Army Research Institute 1 

ATTN: Irv Alderman 
5001 Eisenhower Avenue 
Alexandria, Virginia 22333 

£7. Navel Ocean Systems Center 1 

ATTN: John Phillips, Code 7232 
San Diego, California 92152 

£8. Wayne Lea 1 

£89 Sanford Court 
Santa Barbara, California 93111 

£9. Naval Electronics Systems Center 1 

ATTN: Erank Deckelman, Code 330 
2511 Jefferson Davis Highway 
Arlington, Virginia 20360 

90. Naval Ocean Systems Center 1 

ATTN: Bruno White, Code £302 

San Diego, California 92152 

91. Naval Ocean Systems Center 1 

ATTN: William Dejka, Code 8302 

San Diego, California 92152 


161 








92. Advanced Research Projects Agency/IPTO 1 

ATTN: Lcdr J. Dietzler, USN 

1420 Wilson Blvd. 

Arlington, Virginia 22362 

93. Bolt, Beranek, and Newman, Inc. 1 

ATTN: Richard Pew 

50 houlton Street 

Cambridge, Massachusetts 20138 

94. University of Missouri at Columbia 1 

Industrial Engineering Department 

ATTN: Marlin Thomas 

Room 113, Electrical Engineering Building 
Columbia, Missouri 64211 


95. Office of Naval Research 1 

ATTN: M. Talcott, Code 455 

£00 North Cuincy Street 
Arlington, Virginia 22217 

96. Office of Naval Research 1 

ATTN: G. Maleclci, Code 455 

Arlington, Virginia 22217 

97. Bolt, Beranek, and Newman, Inc. 1 

ATTN: N. Greenfield 

50 Moulton Street 

Cambridge, Massachusetts 02136 

98. Air Force Human Resources Lab/TT 1 

ATTN: Col Richard Shelton, USAF 

Lowry AFB, Colorado 60230 

99. Armed Forces Air Intelligence Training Center 1 

ATTN: Capt Dick Rewalt 

Building 360 

Lcwry AFB, Colorado 60230- 

100. University of Southern California 1 


Information Sciences Institute 

ATTN: R. Bisbey 

4676 Admiralty Way 

Marina Del Ray, California 90291 

101. Naval Ocean Systems Center 1 

ATTN: R. Kolb, Code 624 
San Diego, California 92152 


162 


1 


102. Coinmander in Chief Pacific Fleet 
ATTN: Car R. heinhold, Code £4 
3cx 6 

Pearl Earbcr, Hawaii 96960 

103. Stanford Research Institute 
Artificial Intellignce Center 
ATTN: Daniel Sagalowicz 

33 Ravenswood Avenue 
I^enlo Park, California 94025 

104. Science Applications Incorporated 
ATTN: Russ Hammond 

Suite 1200 

1911 North Fort Meyer Drive 
Arlington, Virginia 22209 

105. S. Parsons 

19740 Via Fscuela Drive 
Saratoga, California 95070 

106. University of Michigan 
Industrial Engineering Department 
ATTN: Don Chaffin 

Ann Arbor, Michigan 4S104 

106. University of Michigan 
Industrial Engineering Department 
ATTN: Walt Hancock 

Ann Arbor, Michigan ^48104 

107. Noval Ocean Systems Center 
ATTN: Dennis hcCall, Code 6242 
San Diego, California 92512 

108. Office of Naval Research 

ATTN: Marvin Denicoff, Code 437 
800 North Quincy Street 
Arlington, Virginia 22217 

109. Naval Ocean Systems Center 
ATTN: John Schill, Code 92152 
San Diego, California 92152 

110. University of Pennsylvania 
Wharton School of Business 
ATTN: E. Morgan 

Room W-63, Dietrich Hall 
Philadelphia, Pennsylvania 19104 


1 

1 

1 

1 

1 

1 

1 

1 

1 


163 



111. Naval Electronics Systems Command 
ATTN: Dan Schutzer, PME 12£ 

2511 Jefferson Davis Highway 
Washington, D.C. 22360 

112. Advanced Research Projects Agency/IPTO 
ATTN: R. Kahn 

1400 Wilson Elvd. 

Arlington, Virginia 22209 

113. Threshold Technology, Inc. 

ATTN : Tom Martin 

1629 Underwood Blvd. 

Delran, New Jersey 06075 

114. Threshold Technology, Inc. 

ATTN: Joe Bove 

lt529 Underwooa Blvd. 

Delran, New Jersey 06075 

115. Threshold Technology, Inc. 

ATTN: Phillips Scott 

1529 Underwood Blvd. 

Delran, New Jersey 06075 

115. Advanced Research Projects Agency/CTO 
ATTN : Craig Fields 
1400 Wilson Blvd. 

Arlington, Virginia 22209 

117. Comm.andant of the Marines 
Scientific Advisor 

ATTN: A. L. Slafkosky, Code RD-1 
Washington, D.C. 20360 

118. Institute for Defense Analysis 
ATTN: Jesse Crlansky 

400 Arny-Navy Drive 
Arlington, Virginia 22202 

119. Naval Ocean Systems Center 
ATTN: Clen Allgaier, Code 6242 
San Diego, California 92152 

120. Air Force Aerospace Medical Research Lah/KEF 
ATTN : Den Topmiller 

Wright Patterson AFB, Chio 45433 


■1 

1 

1 

1 

1 

1 

1 

1 

1 

1 


164 



1 


121. Naval electronics Systems Command 
ATTN: R. Jratilla, Code 330 
2511 Jefferson Davis Highway 
Arlington, Virginia 20360 

122. Naval Electronics Systems Commend 1 

ATTN: J. hachodo, Code 330 

2511 Jefferson Davis Highway 
Arlington, Virginia 20362 

123. Capt John Armstrong 1 

6445 Sugar Creek Way 

Orleans, Ontario 
Canada KIC lYl 

124. Department of National Defence 1 

NDHS DAS Eng. 4 

ATTN: Lt Col J. A. Wellington, CAF 
101 Colonel by Drive 
Ottawa, Ontario 
Canada KIA 0E2 


125. Romie Air Development Center/IRRA 1 

ATTN: R. Vonusa 

Sriffiss AF3, New York 13441 

126. Lt Col r^ark Smith, USAF 1 

9500 Braddock Road 

Fairfax, Virginia 22032 

12?. Computer Corporation of America 1 

ATTN: Chris Eerot 
575 Technology Square 
Cambridge, Massachusetts 02139 

128. Digital Equipment Corporation 1 

ATTN: Paul Thordarson, ML3-2/E41 

146 Main Street 

Maynard, Massachusetts 02139 

129. Thomas J. Watson Researcn Center 1 

ATTN: John Gould 

Box 2lS 

Yorktown Heights, New York 10596 


130. Lockheed Missile and Space Division 1 

Department 86-10 
ATTN: Leon Herman 
Box 182 
Building 504 


165 


Sunnyvale, California 94266 

131. Biotechnology, Inc. 1 

ATTN: Harold Price 

3027 Rosemary Lane 

Falls Church, Virginia 22042 

132. f'iaj Warren Watkins, USAF 1 

1 STRAD/D02 

Vandenburg AFE, California 93437 

133. Olin Campbell 1 

Suite 201 

1150 South State Street 
Orem, Utah 84057 

134. Commander in Chief Pacific Fleet 1 

TRW Field Office 

ATTN: George Harris, Code N-34 
Pearl Harbor, HI 96860 

135. Air Force Aerospace Medical Research Lab/HFC 1 

ATTN: Lew Hahn 

Wright-Patterson AFB, Ohio 45433 

136. California Institute of Technology 1 

Jet Propulsion Laboratory 

Systems Analysis Section 
ATTN: Robert L. Sohn 
4600 Oak Grove Drive 
Pasadena, California 91103 

137. Massachusetts Institute of Technology 1 

Lincoln Laboratories 

ATTN : Cliff Weinstein 
Room B-335 

Lexington, Massachusetts 02173 

138. David Jcly 1 

2180 Bryant Street 

San Francisco, California 94110 

139. Naval Training Equipment Center 1 

Human Factors Laboratory 

ATTN: Elizabeth Lambert, Code N-711 
Orlando, Florida 32813 


166 


1 


140. Threshold Technclcsy, Incorporated 
ATTN: Fred Gladney 
Suite 4 - Cl 

1440 South State College 31vl. 

Anaheim, California 92606 

141. Heuristics, Inc. 1 

ATTN : Tom Imperato 

1285 Hammerwood Avenue 
Sunnyvale, California 94266 

142. XYBICN 1 

ATTN: Paul Frost 

7 Ridgedale Avenue 

Cedar Knolls, New Jersey 07927 

143. Threshold Technology, Incorporated 1 

ATTN: John V/elch 

1829 Underwood Elvd. 

Delran, New Jersey 26075 

144. Cffice of Naval Research 1 

ATTN: Robert Wisher, Code 456 

800 North Quincy Street 
Arlington, Virginia 22217 

145. Honeywell, Incorporated 1 

Systems and Researcn Center 

ATTN: Robert North 
2600 Ridgeway Elvd. 

Minneapolis, Minnesota 55413 

146. National Bureau of Standards 1 

Information-Communications Systems Technology 

ATTN: Dave Pa 11ett 
A219 Technology Building 
Washington, D.C. 22234 


167 


i 








5 




Thesis 

J345 

c.l 


Jay 


i 



192411 

An experiment in 
yoice data entry for 

'"lagery interpretation 
reporting. 


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Thes is 192411 

J345 Jay 

c.l An experiment in 

voice data entry for 
imagery interpretation 
reporting.