Naval Submarine Medical Research Laboratory

NSMRL Report 1165 10 December 1990

CONTRIBUTIONS OF ENVELOPE INFORMATION

TO CLASSIFICATION OF BRIEF SOUNDS

Thomas E. Hanna

Released by:

R. G. Walter, CAPT, DC, USN

Commanding Officer

Naval Submarine Medical Research Laboratory

Approved for public release; distribution unlimited
CONTRIBUTIONS OF ENVELOPE INFORMATION

TO CLASSIFICATION OF BRIEF SOUNDS

Thomas E. Hanna

NAVAL SUBMARINE MEDICAL RESEARCH LABORATORY

NSMRL REPORT 1165

OFFICE OF NAVAL RESEARCH

RESEARCH WORK UNIT 61153N - RR4209.001-ONR4424207

Approved and released by

R. G. WALTER CAPT, DC, USN

Commanding Officer

NavSubMedRschLab

Approved for public release; distribution unlimited
SUMMARY PAGE

THE PROBLEM

To identify the potential relevance of the signal envelope for aural classification.

THE FINDINGS

Listeners were trained to classify a set of sounds into eight categories. Classification was

almost as good in subsequent tasks where listeners classified signal envelopes or signals

created by modulating a tone with the signal envelopes. Classification of signals created

by modulating a tonal-complex or broadband noise was markedly worse, probably due to

interaction of sidebands from nearby carrier frequencies.

APPLICATION

These results indicate that further investigation of envelope features and aural sensitivity

to these features would further our understanding of aural classification of brief complex

sounds.

ADMINISTRATIVE INFORMATION

This investigation was conducted under Office of Naval Research Work Unit 61153NRR4209.001-ONR4424207. It was submitted for review on 18 January 1990, approved

for publication on 10 December 1990, and designated Naval Submarine Medical Research Report 1165.

ii
ABSTRACT

Listeners were trained to classify a set of sounds into eight

categories. Classification was almost as good in subsequent tasks where

listeners classified signal envelopes or signals created by modulating a tone

with the signal envelopes. Classification of signals created by modulating a

tonal-complex or broadband noise was markedly worse, probably due to

interaction of sidebands from nearby carrier frequencies. These results

suggest the importance of envelope cues for aural classification. Further

investigation of envelope features and aural sensitivity to these features

would further our understanding of aural classification of brief complex

sounds.

iii
Most psychoacoustic research has concentrated on describing the auditory

system's ability to detect signals or to discriminate small changes in simple

stimuli such as tones or bands of noise. More recently, increasing attention

is being paid to the auditory system's ability to classify sounds so that we

can better understand the acoustic features that underlie aural recognition of

complex real-world sounds. Many acoustic features are potentially available

within the auditory system, but an analysis of some of these features can be

simplified by considering one aspect of the acoustic waveform - the amplitude

envelope. The signal envelope is an amplitude-time function that describes

the signal's amplitude variation distinct from the spectral content. Thus,

for example, a two-tone signal consisting of 500 and 504 Hz would produce a

"beating" sensation due to its periodic 4 Hz amplitude variation, as

would a two-tone signal consisting of 800 and 804 Hz or any pair of

frequencies separated by 4 Hz.

Using two-tone complexes, Buus (1983) has shown that the auditory system

can discriminate envelope fluctuations up to at least 640 Hz. Using a noise

carrier modulated by the speech envelope, Van Tassell et al. (1987) have shown

that envelope frequencies less than 200 Hz (and possibly higher) provide the

information needed for the discrimination of certain speech features. The

present study examines the role of the envelope for the perception of

nonspeech sounds.

METHOD

Signals. Fifty one-second segments were extracted from digitized recordings

of underwater sounds. Each segment contained an event with a duration ranging

from tens to hundreds of milliseconds. Each event was approximately centered

within the one-second sample. The recordings had been digitized at a 12.5 kHz

sampling rate with 12 bits of linear encoding of amplitude. A preliminary

classification of the fifty events into eight categories was performed based

on transcripts of the recording sessions and in consultation with two

experienced sonar operators who listened to the recordings in their original

context (prior to extraction). For each of the eight categories, three

exemplars were chosen that represented good-quality samples with minimal

ambiguity regarding the accuracy of the classification.

Classification performance was measured using the original set of fifty

signals and four other sets that were derived from the signal envelopes of the

original set. Envelopes were extracted from the digitized signals using

the Interactive Laboratory System (ILS) from Signal Technology Inc. In the

first of the envelope conditions, the fifty envelopes were used as signals,

i.e., the envelope was presented as a time waveform; in the second condition,

the envelopes were used to modulate a multitonal complex consisting of tones

with approximately one-third octave spacing; in the third condition, the

envelopes were used to modulate a broadband noise carrier; and in the fourth

condition, the envelopes were used to modulate a 3-kHz tonal carrier.

Apparatus. For the condition with the original set of signals and for the

first of the envelope conditions, the sounds were presented over 16-bit

digital-to-analog converters with a 12.5 kHz sampling rate. Stimuli were

1
low-pass filtered at 5 kHz. All filters in this experiment had asymptotic

rejection rates of 115 dB/octave.

In the modulated-carrier conditions, the envelope was presented over 16-

bit digital-to-analog converters and low-pass filtered at 5 kHz (3 kHz for the

tonal carrier). The carriers for the three conditions were: 1) a tonalcomplex, consisting of 500, 650, 800, 1000, 1250, 1600, 2000, 2500, 3150,

4000, and 5000 Hz tones (with arbitrary starting phases), which was presented

over a second digital-to-analog converter, 2) broadband noise, generated from

a white-noise generator and filtered from 0.5 to 5.0 kHz, and 3) a 3-kHz tone,

generated from an oscillator. The carrier was multiplied by the envelope and

filtered from 0.5 to 5.0 kHz (0 to 6 kHz for the tone carrier).

In all conditions a programmable attenuator was used to adjust the

amplitude of each signal to a comfortable listening level. In addition, the

programmable attenuator was used to randomize stimulus levels over a 15-dB

range to minimize the use of amplitude as a classification cue. An electronic

switch gated the stimuli with 20-ms, sine-squared ramping. Stimuli were

presented to the right earphone of a Sennheiser HD430 headset.

Procedure.

Table I shows the order of the training and testing phases.

Table I

Order of training and testing.

Initial training

Training for condition 1

Testing for condition 1

Training for condition 2

Testing for condition 2

Retesting of condition 1

Training for condition 3

Testing for condition 3

Retesting of condition 1

Training for condition 4

Testing for condition 4

Retesting of condition 1

Training for condition 5

Testing for condition 5

(original signals)

(envelopes)

(exemplars only)

(modulated tone complex)

(exemplars only)

(modulated noise)

(exemplars only)

(modulated tone)

Initial training: On each trial, one stimulus was presented and the

listener classified it using the letters A-H to designate the eight

categories. The correct response was displayed after each response. Only the

exemplars from categories one through four were presented within half of

the blocks and only exemplars from categories five through eight were

presented within the other blocks. These reduced sets were used to facilitate

the learning of category labels. Listeners had at least 670 trials for each

2
of these two stimulus sets by which time they had attained stable performance.

Following initial training, condition-specific training and testing occurred

for the five conditions sequentially.

Condition-specific training: For each condition, listeners were trained

with the full set of eight categories. Only the three exemplars from each

category were presented during this training, and correct-answer feedback was

given on each trial. One day of training, consisting of at least 720 trials,

was conducted prior to switching to the test condition.

Testing: Each of the fifty stimuli was presented once within a block of

fifty trials. If an exemplar was presented, correct-answer feedback was

given. However, if the stimulus was one of the twenty-six stimuli that was

not an exemplar (such stimuli will be called probe stimuli), no feedback was

given. Normally thirty-six blocks of fifty trials were administered during

the test phase. These blocks were run over two days.

All listeners were tested simultaneously which prevented

counterbalancing the conditions across listeners. Conditions were run in the

following order: original sonar signals, envelopes, modulated tone-complex,

modulated noise, and modulated tone. Before each of the modulated-carrier

conditions, listeners were retested on the original set of signals for one

session (approximately 864 trials) to monitor performance in this baseline

condition. Only exemplars were used for retesting.

Listeners. Three paid volunteers and the author (identified as L2 in the

Tables) served as listeners. Each had normal hearing sensitivity (less than

15 dB HL at octave frequencies from 250 to 8000 Hz). The author had been

involved in the stimulus preparation and was very familiar with the signals

prior to testing. The other three subjects had never heard these sounds prior

to this experiment.

RESULTS

Table II shows percent correct on the original signals. Performance is

stable except for a small improvement for Li. L4's performance is markedly

poorer than the other three listeners -- even after thousands of trials with

these signals L4 only achieved 65% correct while the other three listeners got

more than 90% correct.

Table II

Percent correct classification on initial and retested conditions using the

original signals for each of four listeners. The three retestings were prior

to each of the modulated carrier conditions.

Listeners

Li L2 L3 L4

Initial test 89.4 99.6 88.4 65.4

First retest 95.6 -- 91.1 70.8

Second retest 94.6 .. .. 65.4

Third retest 96.6 -. .. 64.1

3
Table III shows the percent correct on the 24 exemplars and the percent

correct for 18 of the probe stimuli for each condition. Eight of the probe

stimuli were eliminated from this analysis because they were poor recordings

or contained artifacts that created ambiguity about which event was to be

judged. Five of these eight stimuli had been identified in a previous study

(Hanna, 1989); three additional stimuli with similar problems were identified

after examining listeners' responses to the original (unaltered) signals of

the present study. The inconsistency of listeners' responses to these stimuli

was clearly attributable to the quality of the signal. Apparently three of

these stimuli were not identified in the previous study due to those two

listeners' prior familiarity with the signals.

Table III

Percent correct classification of exemplar and probe signals in each of the

five conditions and for each of four listeners.

Exemplars:

Listeners

Li L2 L3 L4

Original 89.4 99.6 88.4 65.4

Envelope 84.7 -- 76.6 51.1

Modulated tone 85.8 91.9 -- 27.0

Modulated complex 69.3 --.. 20.0

Modulated noise 66.4 57.7 .. ..

Probes:

Listeners

Li L2 L3 L4

Original 69.4 82.6 67.9 45.8

Envelope 65.4 -- 57.7 37.8

Modulated tone 60.1 69.5 -- 18.4

Modulated complex 41.5 .. .. 20.2

Modulated noise 40.7 36.0 .. ..

Percents correct on the probe stimuli are roughly 20% less than on the

exemplars. This difference is presumably a reflection of t'ie fact that the

clearest and least ambiguous signals were used as exemplars. It appears that,

for each condition, listeners appropriately generalize the categories to the

probe stimuli even though they have never been given feedback about the probe

stimuli. This result indicates that listeners are learning categories rather

than simply learning arbitrary assignments of category labels to each of the

exemplar stimuli.

With two minor exceptions, performance on the five conditions is rankordered similarly for each listener and for both exemplar and probe stimuli.

Classification is best on the original (unaltered) set of signals, followed by

the envelope condition, the modulated tone condition, the modulated tonalcomplex condition, and the modulated broadband-noise condition. Listener 4 is

noticeably worse than the other three listeners, particularly for the

modulated-carrier conditions.

4
Performance in the envelope condition was almost as good as for the

original signals. Percent correct was only 4-14% worse when the envelope was

presented as the signal. Moreover, the envelope signals sounded remarkably

similar to the original signals. For two of three listeners for which a

comparison is possible, performance on the modulated-tone condition is also

almost as good as for the original signals. For these two listeners (LI &

L2), percent correct was only 4-13% worse with the modulated tone. The other

listener (L4) was the one that did poorly (near chance) in all of the

modulated-carrier conditions. All listeners showed a marked decrement with

the modulated tonal-complex and the modulated noise carriers. Percent correct

was 20-46% worse in these two conditions than for the original signals.

Although performance was noticeably worse for these two conditions it should

still be noted that Li & L2 still got 36-69% percent correct with these

signals (versus chance performance of 12.5%).

Table IV shows the pattern of errors made by Li for whom we have data

for all conditions. This table shows the percentage of times each response

was given to the exemplar signals from each of the eight categories. For the

envelope and modulated-tone conditions, categories 3, 6, and 8 are the ones

that show the largest decrements relative to the original signals. Most of

the increase in errors is attributable to these three categories. These

results suggest that the envelope does not contain all of the information by

which listeners distinguished categories 3, 6, and 8. For the modulated

tonal-complex and modulated noise conditions, decrements are found for

categories 1, 3, 4, 6, 7, and 8. The errors among stimuli from categories 1,

3, 6, and 8 are common. These errors include those made in the envelope and

modulated-tone conditions as well as additional errors involving categories 1,

4, and 7. Thus, the conditions do not idiosyncratically degrade the

signals--the conditions may be rank-ordered not only by overall level of

performance but also by the types and amount of information that are affected

in the various conditions. The information lost (or masked) in the

modulated-tonal-complex and modulated-noise conditions is in addition to that

lost (or masked) in the envelope and modulated-tone conditions.

We analyzed the patterns of errors using Multidimensional Scaling (MDS) in

order to identify perceptual dimensions underlying the classification of these

sounds (Kruskal & Wish, 1978). MDS is a scaling technique that places stimuli

in a multidimensional space such that the closeness of two points in the space

is correlated with the perceived similarity of the two stimuli. For our data,

the similarity, S(i,j), of stimuli i and j was defined as:

8

S(ij) = I p(ik)p(jk) (1)

k=l

where p(i,k) is the probability that stimulus i will be called category k.

5
Table IV

Confusion matrix for Li for each of the five conditions. Each entry

represents the percentage of times this listener gave a particular response to

exemplar signals from a given category.

Original signals:

Response

1 2 3 4 5 6 7 8

Signal cat.

1 99

2 1

3

4

5

6

7

8

Envelope:

Signal cat.

1 94

2

3 2

4 1

5

6 5

7

8 1

Response

1 2 3 4

75

19

2

5 6 7 8

- 1 - 4

20 - - 4

70 2 - 5 - 98 - -

- - 100 -

1 - - 72

3 6 - 19

Modulated tone:

Response

1 2 3 4

Signal cat.

1 96

2 1

3 5

4

5

6 2

7

8 3

87

13

2

15

1

3

1

98

1

1

23

72

5 6 7 8

2 - - 2

7 1 - 1

68 - - 10

- 100 - -

- - 100 -

7 - - 76

16 - - 7

3

1

4

100

3

9

59

6

64

8

31 1

80 3

- 96

3

8

4

1

99

1

92

10

- 100

4 1

1

3

1

3

86 1
Modulated tonal-complex:

Response

1 2 3 4 5 6 7 8

Signal cat.

1 67 3 18 - - 1 1 10

2 4 75 21 - - - -

3 13 16 44 1 - 4 2 20

4 - - - 92 1 - - 7

5 - - - 4 95 1 - -

6 5 3 14 3 - 44 7 24

7 1 6 13 1 1 1 77 -

8 1 - 3 21 - 11 2 62

Modulated broadband-noise:

Response

1 2 3 4 5 6 7 8

Signal cat.

1 61 6 15 - - 11 1 6

2 7 88 1 2 - - 2 -

3 13 10 39 13 - 14 4 6

4 3 - 1 78 2 4 2 10

5 - - - 1 98 - 1 -

6 10 6 18 5 - 46 4 11

7 6 9 3 - - 1 81 -

8 10 2 4 16 - 22 4 41

7
MDS REPRESENTATION FOR 24 EXEMPLARS

0.50

CATEGORY

SA I

z 0 0 2

0 0.25 0 0 0 3

V 4

,,"- <> 5

* 6

S0.00 - 7

+ + 8

-0.25

-0.25 0.00 0.25 0.50

MDS DIMENSION I

0.50

CATEGORY

SA A I

z C3 2

o 0.25 0 3

U)• 4 z

u< > 5

*• 6

C, 0.00- 0 7

U--- )• - + 8

-0.25

I , I , I I

-0.25 0.00 0.25 0.50

MDS DIMENSION 2

Figure 1. SINDSCAL representation for the twenty-four exemplars. Fig. la

plots values on Dimension 4 vs. values on Dimension 1; Fig. lb plots values on

Dimension 3 vs. values on Dimension 2. The different symbols represent the

eight different stimulus categories. Three exemplars from each category are

shown.

8
This summed crossproduct corresponds to the probability that the two stimuli

would be given the same category label, assuming independent responses to

each. Similarity matrices defined by Eq. 1 were constructed separately for

each listener and condition. A SINDSCAL MDS analysis (Carroll & Chang, 1970)

of these fourteen matrices (corresponding to condition by listener entries in

Table III) produces a common perceptual space and a weightings space that

indicates differential weighting of the dimensions for the fourteen similarity

matrices.

A four-dimensional solution accounted for 61.3% of the variance. Higherdimensional solutions provided only a moderately better fit (65.4% and 67.3%

for five- and six-dimensional solutions, respectively). Decreasing the

dimensionality to three caused a larger change in explained variance, down to

52.2%. Using the typical criterion for dimensionality, we took the relatively

sharp decrement in explained variance as dimensionality decreased from four to

three as an indication that four dimensions are appropriate to describe the

data. This solution uses about 256 parameters (4 dimension values for 50

stimuli plus 4 weights for 14 matrices) to predict 5600 data values (8

response probabilities for 50 stimuli for 14 matrices). Repeated analyses

with different starting configurations gave similar results.

Figure 1 shows the obtained SINDSCAL representation. Figure la plots

values on MDS dimensions 1 and 4; Figure lb plots MDS dimensions 2 and 3.

Each point represents a single stimulus. For clarity only the 24 exemplars

are shown. Different symbols are used for each of the eight stimulus

categories. Each symbol appears three times in each plot to represent the

three exemplars from each category.

WEIGHTING COEFFICIENTS FOR FOUR LISTENERS

0.6

W -7

W 0 LISTENERS

U 0.4- -__ LI

W - " 0 L2

O 0 30 0L3 0.3- _ OL

o _ V L4

z

p0.2-

S0.I

0.0 I I I I

I 2 3 4

MDS DIMENSION NO.

Figure 2. Dimensional weighting coefficients for the classification of the

original signals. The different symbols represent the four listeners.

9
Examination of how stimuli varied along the individual dimensions

suggested perceptual correlates for each of the four dimensions (the first

attribute corresponds to a positive value on the given dimension): Dimension

1 - heavy vs. light, Dimension 2 - rough vs. nonrough, Dimension 3 -

extended vs. compact in duration, Dimension 4 - soft vs. hard.

Figure 2 shows the dimension weights for individual listeners for the

original signals. LI, L2, and L3 have similar weightings, but L4 gives a much

lower weight to Dimension 4. L4's lower performance can be attributed to an

insensitivity to this dimension. Figure 3 shows the dimension weights for Li

for each of the five conditions. Again, Dimension 4 shows the greatest

differences, with greatly reduced weight in the modulated tone condition and

almost no weight in the modulated tonal-complex and the modulated-noise

conditions. In addition, Dimension 3 receives less weight in the modulated

tonal-complex and modulated-noise conditions. These decreases in weights can

be interpreted as a reduction or masking of the cues underlying these

dimensions. This reduced sensitivity to Dimensions 3 and 4 is compensated for

by a relatively greater weight given Dimensions 1 and 2. These results are

consistent with the conclusion that the cues lost in the modulated-tonalcomplex and modulated-noise conditions are in addition to those lost in the

envelope and modulated-tone conditions.

WEIGHTING COEFFICIENTS FOR FIVE CONDITIONS

I 2 3 4

CONDITIONS

A ORIG

El ENVE

0 TONE

V COMP

4> NOIS

MDS DIMENSION NO.

Figure 3. Dimensional weighting coefficients for LI. The different symbols

represent the five stimulus conditions.

10

0.6

I I I I

I--

z

wLi

(0

U

u_

U~_

0

z

UI

o

0.5-

0.41-

0.31-

0.2[-

O.I --

0.0

I I I I

I I I
DISCUSSION

Although the number of listeners and conditions tested in this current

study are limited, the results serve to demonstrate that envelope features may

have a very significant role for aural classification of brief nonspeech

sounds. As indicated by performance in the envelope and modulated-tone

conditions, sufficient information exists in the envelope to classify these

brief nonspeech sounds very well. It would seem that the very low modulation

rates, less than 80 Hz, are not critical because listeners could classify

signals in the envelope condition where frequencies less than 80 Hz are

relatively inaudible. However, low modulation rates may still be very

important after including auditory processing effects. The auditory system

may be insensitive to modulation rates of 800 and 820 Hz, but easily hear the

20 Hz intermodulation which exists between them. Thus, low frequency

modulation that is not present as a discrete component may be carried by high

frequency modulation rates.

The poorer performance in the modulated tonal-complex and modulated

broadband-noise conditions is likely due to interaction of sidebands from

nearby carrier frequencies. For low modulation rates, perhaps less than 50

Hz, these interactions would probably not interfere much with the coherent

modulation of the carrier frequencies. For larger modulation rates, the

sidebands will be distributed widely, producing complex sets of

intermodulations at modulation rates that are lower than the coherent

modulation. The effects of critical band filtering and limited temporal

resolution would provide greater emphasis to the intermodulations than the

coherent modulation, resulting in a significantly different modulation pattern

than in the original signal. These interactions would also reduce the

modulation depth of the envelope and make its lower-frequency components less

discernable. Whether the poorer performance with these broadband carriers is

due to the loss of the higher modulation rates or simply the masking of the

lower modulation rates remains to be determined.

The SINDSCAL analysis provided four dimensions with perceptual correlates

that are potentially related to sound source properties, such as hardness or

weight. Gibson (1979) suggested that perceptual information is organized

according to its specification of object properties. The current results are

consistent with Gibson's theory. Warren and Verbrugge (1984) and Richards and

Ullman (1988) also suggest that temporal features can provide information

about object properties. A psychoacoustic theory of classification would

specify the acoustic features by which object properties are auditorily

determined. Results with the modulated carriers are first steps towards

identifying acoustic correlates in that the presence of Dimension 3 and 4 cues

are significantly reduced. Apparently the sideband interactions with

broadband carriers affected the cues underlying Dimension 3 and 4 but not

those cues underlying Dimensions 1 & 2.

In summary, four dimensions have been identified for aural classification

of a set of brief underwater signals. Various methods of presenting envelope

information aurally suggest that the envelope contains important features for

aural classification of these signals. Listeners were insensitive to some of

these features under certain modulated-carrier conditions, but an acoustic

11
analysis of the important envelope features and modulation rates will

require further data and reference to auditory models of modulation

sensitivity.

12
ACKNOWLEDGMENTS

This research was supported by the Perceptual Sciences Program of the

Office of Naval Research. I thank Dr. Tom Santoro and Lee Shapiro for writing

signal-editing and experimental programs; Sue Carpenter for collecting the

data and assisting with the data analysis; and Drs. Jerry Tobias and Paul

Weathersby for comments on drafts of the manuscript.

DISCLAIMER

The views expressed in this article are those of the author and do not

necessarily reflect the official policy or position of the Dept. of the Navy,

Dept. of Defense, or the U.S. Government.

13
REFERENCES

Buus, S. (1983) Discrimination of envelope frequency, Journal of the

Acoustical Society of America 74, 1709-1715.

Carroll, J. D., & Chang, J. J. (1970). Analysis of individual differences in

multidimensional scaling via an N-way generalization of 'Eckart-Young'

decomposition, Psychometrika 35, 283-319.

Gibson, J. J. (1979). The ecological approach to visual perception. Boston:

Houghton Mifflin.

Hanna, T. E. (1989). Preliminary report on classification of transient sonar

signals, Naval Submarine Medical Research Laboratory Report No. 1142.

Kruskal, J. B., & Wish, M. (1978). Multidimensional Scaling. Eleventh in the

Series: Quantitative Applications in the Social Sciences (E. M. Uslaner,

Ed.), Sage Publications: Beverly Hills, CA.

Richards, W., & Ullman, S. (1988). Inferences from images: (Final Report

1984-1987) ONR Contract N00014-84-K-0650, pp. 90-100.

Van Tassell, D. J., Soli, S. D., Kirby, V. M., and Widin, G. P. (1987).

Speech waveform envelope cues for consonant recognition, Journal of the

Acoustical Society of America 82, 1152-1161.

Warren, W. H., Jr., and Verbrugge, R. R. (1984). Auditory perception of

breaking and bouncing events: A case study in ecological acoustics.

Journal of Experimental Psychology: Human Perception and Performance

10, 704-712.

14
ONR DISTRIBUTION LIST

Perceptual Science Program

OUSDR (A)/R&A(E&LS)

Pentagon 3D129

Washington, DC 20301-3080

Dr. Alan D. Baddeley

Director, Appl. Psychol. Unit

Medical Research Council

15 Chaucer Road

Cambridge CB2 2EF

ENGLAND

Dr. Bruce Barnes

Program Director, Div. Info

Robotics, & Intell. Systems

National Science Foundation

1800 G Street, N.W.

Washington, DC 20550

Mr. Charles Bates

Director, HE Division

USAF AAMRL/HE

WPAFB, OH 45433

Mr. Norman Beck

Naval Underwater Systems

Center

Combat Control Systems

Department Code 221

Newport, RI 02840

Dr. Kenneth R. Boff

AAMRL/HE

WPAFB, OH 45433

Mr. Luiz Cabral

Naval Underwater Sys. Ctr.

Code 2212

Bldg. 1171/1

Newport, RI 02841

Cdr. Robert C. Carter USN

Naval Research Laboratory

Code 5532

Washington, DC 20375-5000

Dr. David Castanon

Alphatech, Inc.

111 Middlesex Turnpike

Burlington, MA 01803

Dr. Marvin S. Cohen

Dec. Sci. Consortium, Inc.

1895 Preston White Drive

Suite 300

Reston, VA 22091

Dr. Stanley C. Collyer

Office of Naval Technology

Code 222

800 N. Quincy Street

Arlington, VA 22217-5000

Defense Tech. Info. Center

Cameron Station, Bldg 5

Alexandria, VA 22314

(2 copies)

Mr. Dan Greenwood

Netrologic, Inc.

5080 Shoreham Place

Suite 201

San Diego, CA 92122

Jeffrey Grossman

Naval Ocean Systems Center

Code 4402

Bldg. 334

San Diego, CA 92152

Dr. Steven Hillyard

Univ of Calif - San Diego

Department of Neuroscience

La Jolla, CA 92093

Prof. James H. Howard, Jr.

Department of Psychology

Human Performance Lab

Catholic University

Washington, DC 20064

Dr. Edgar M. Johnson

Technical Director

US Army Research Institute

5001 Eisenhower Avenue

Alexandria, VA 22333-5600

Capt T. E. Jones, MSC, USN

Aviation Medicine & Human

Performance (Code 404)

Naval Medical R & D Cmd

National Capital Region

Bethesda, MD 21814-5044

Dr. Michael Kaplan,

Director, Office Basic Res

US Army Research Institute

5001 Eisenhower Avenue

Alexandria, VA 22333-5600

Prof. David L. Kleinman

Electrical Engineering &

Computer Science Dept.

University of Connecticut

Storrs, CT 06268

Mr. Keith Kramer

Naval Research Laboratory

Code 5532

Washington, DC 20375-5000

Dr. Richard Loutitt

National Science Foundation

Division of Behavioral &

Neural Sciences

1800 G Street, N. W.

Washington, DC 20550

Capt. William Moroney, USN

Naval Air Development Ctr.

Code 602

Warminster, PA 18974

Dean of the Academic Dept.

U. S. Naval Academy

Annapolis, MD 21402-5018

15
Naval Aerospace Medical

Research Laboratory

Sensory Division Code 23

Pensacola, FL 32508

Commanding Officer

Naval Air Systems Command

Crew Station Design

NAVAIR 5313

Washington, DC 20361

Commanding Officer

Naval Biodynamics Lab

Michoud Station

Box 29407

New Orleans, LA 70189

Commanding Officer

Navy Health Research Ctr.

P.O. Box 85122

San Diego, CA 92138

Commanding Officer

Navy Personnel R&D Center

San Diego, CA 92152-6800

Director

Technical Information Div.

Code 2627

Naval Research Laboratory

Washington, DC 20375-5000

US Naval Test Center

Aircrew Systems Branch

Systems Engineering Test

Directorate

Patuxent River, MD 20670

Commanding Officer

Naval Weapons Center

Human Factors Branch

Code 3152

China Lake, CA 93555

Dr. Michael Letsky

Office of the Chief of

Naval Operations

OP-01B7

Washington, DC 20350

Office of the Chief of

Naval Operations

OP-933D3

Washington, DC 20350-2000

Office of Naval Research

Special Asst. for Marine

Corps Matters

Code OOMC

800 N. Quincy Street

Arlington, VA 22217-5000

Office of Naval Research

Perceptual Science Program

Code 1142PS

800 N. Quincy Street

Arlington, VA 22217-5000

(3 copies)

Dr. W. A. Rizzo

Head, Human Factors Div.

Naval Training Systems Ctr

12350 Research Parkway

Orlando, FL 32826-3224

Prof. James A. Simmons

Department of Psychology

Brown University

Providence, RI 02912

Dr. H. Wallace Sinaiko

Manpower Research 

&

Advisory Services

Smithsonian Institution

801 N. Pitt St. Suite 120

Alexandria, VA 22314-1713

LCdr. Timothy Singer, USN

Naval Air Development Ctr.

Human Factors Engrg. Div.

Warminster, PA 18974

Mr. James G. Smith

Office of Naval Research

Code 121

800 N. Quincy Street

Arlington, VA 22217-5000

Cdr. S. Snyder

Office of Naval Technology

Code 222

800 N. Quincy Street

Arlington, VA 22217-5000

Dr. George Sperling

Department of Psychology

6 Washington Place

New York, NY 10003

Mr. Nelson F. Steele

Advanced Res Dev Corp

9151 Rumsey Road

Columbia, MD 21045

Dr. John Tangney

AF Office of Sci. Res.

Life Sciences Directorate

Bldg. 410

Bolling AFB, DC 20332-6448

Dr. Ronald J. Tusa

Johns Hopkins University

Neurology Department

34th & Charles Place

Baltimore, MD 21218

Dr. Harold P. Van Cott

Committee on Human Factors

NAS-National Res. Council

2101 Constitution Ave, N.W.

Washington, DC 20418

Dr. Charles S. Weaver

MAXIM Technologies, Inc.

3000 Patrick Henry Drive

Santa Clara, CA 95054

Dr. John Weisz

Technical Director

US Army Human Engineering

Laboratory

Aberdeen P. G., MD 21005

Dr. Milton A. Whitcomb

NAS-National Res. Council

CHABA

2101 Constitution Ave., N.W.

Washington, DC 20418

Prof. Christopher D. Wickens

Departrr nt of Psychology

University of Illinois

C',ampaign, IL 61801

Dr. Wayne Zachary

CHI Systems, Inc.

Gwynedd Plaza III

Bethlehem Pike

Spring House, PA 19477

16
UNCLASSIFIED

SECURITY CLASSIFICATION OF THIS PAGE

Form Approved

REPORT DOCUMENTATION PAGE OMB No 0704-0188

la REPORT SECURITY CLASSIFICATION lb RESTRICTIVE MARKINGS

Unclassified N. A.

2a SECURITY CLASSIFICATION AUTHORITY 3 DISTRIBUTION/AVAILABILITY OF RFPORT

N. A. Approved for public release;

2b DECLASSIFICATION / DOWNGRADING SCHEDULE dis tribution unlimited.

N. A.

4 PERFORMING ORGANIZAT:ON REPORT NUMBER(S) 5 MONITORING ORGANIZATION 'KPORI %NUMBEI(S)

NSMRL Report No. Same

6a NAME OF PERFORMING ORGANIZATION 6b OFFICE SYMBOL 7a NAME OF MONITOfiNC' ORijAMIZATiON

Naval Submarine Medical (If applicable)

Research Laboratory Office of Naval Research

6c. ADDRESS (City, State, and ZIP Code) 7b ADDRESS (City, State/ and ZIP Code)

Naval Submarine Base- New London Box 900 800 N. Quincy Street

tox 90 , Arlington, VA 22217-5000

Groton. CT 06349-,5900 ._____________________

8a NAME OF FUNDING /SPONSORING 8b OFFICE SYMBOL 9 PROCUREM,"AENI INS'RF.;MENT D,'NTIFICArToN NIJMBTR

ORGANIZATION (If applicable)

Office of Naval Research Code 1142PS N00014-88-WR24003

8c. ADDRESS (City, State, and ZIP Code) 10 SOURCE OF FUNDING NUMBERS

800 N. Quincy Street PROGRAM IPROJECT TASK WORK UNIT

ELEMENT NO NO NO ACCESSION NO

Arlington, VA 22217-5000 61153N 42 RR 04209 IR0420901 IR&T4424207

11. TITLE (Include Security Classification)

(U) Contributions of envelope information to classification of brief sounds

12 PERSONAL AUTHOR(S)

Thomas E. Hanna

13a. TYPE OF REPORT 13b TIME COVERED 14 DATE OF REPORT (Year, Month, Day) 15 PAGE COUNT

TechnicalI FROKB47!0!01TO 90/09/3I 1990 December 10 16

16 SUPPLEMENTARY NOTATION

17 COSA'I CODES 18. SUBJECT TERMS (Continue on ieverse if necessary and identify by block number)

FIELD GROUP SUB-GROUP Auditory perception; Aural classification;

Envelope features; Sonar signals

19 ABSTRACT (Continue on reverse if necessary and identify by block number)

Listeners were trained to classify a set of sounds into eight categories. Classification

was almost as good in subsequent tasks where listeners classified signal envelopes or

signals created by modulating a tone with the signal envelopes. Classification of signal

created by modulating a tonal-complex or broadband noise was markedly worse, probably du(

to interaction of sidebands from nearby carrier frequencies. These results suggest the

importance of envelope cues for aural classification. Further investigation of envelope

features and aural sensitivity to these features would further our understanding of

aural classification of brief complex sounds.

20 DISTRIBIJTION /AVAILABILITY OF ABSTRACT 21 ABSIRACT SECURITY CIASS!FCATION

l UNCLASSIFIED/UNLIMITED T) SAME AS RPT E0 DTIC USERS Unclassified

22a NAME OF RESPONSIBLE INDIVIDUAL 22b TELEPHONE (Include Area Code& 22c 10-Ci FSYYMlJU.

.Tohn .1 O'Hqirp .202) 696--4502 cndg 11&I2Pq

DD Form1473, JUN 86 Previous editions are obsolete.

S/N 0102-LF-014-6603

____UCL ASSI ( FLi:CDT'(i 0 ,

UNCLASSIFIED
SECURITY CLASSIFICATION OF THIS PAGE

ODDForml1473:, SF-L;HI TY CLASIFICATION 01: HIS PAGE JUN 86 (Reversýý)