Naval Submarine Medical Research Laboratory

NSMRL REPORT 1171 12 JULY 1991

NARROWBAND

FOR

AND BROADBAND ENVELOPE CUES

AURAL CLASSIFICATION

by

Thomas E. Hanna

and

Yvonne R. Masakowski

Released by:

R. G. Walter, CAPT, DC, USN

Commanding Officer

Naval Submarine Medical Research Laboratory

Approved for public release; distribution unlimited
Narrowband and Broadband Envelope Cues

for Aural Classification

by

Thomas E. Hanna

and

Yvonne R. Masakowski

Naval Submarine Medical Research Laboratory

Report 1171

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

PROBLEM

To determine whether auditory envelope features used to classify brief sounds are

derived from narrowband or broadband analyses of the acoustic signal and the extent to

which higher modulation rates contribute to these envelope features.

FINDINGS

The signal envelope could account for all of the perceptual dimensions needed by listeners to classify a set of brief sounds. These perceptual dimensions were better accounted for by a narrowband analysis of the signal than by a broadband analysis.

Modulation rates above 200 Hz did not contribute much to classification although there

was some suggestion that rates greater than 200 Hz were significant for one of the dimensions.

APPLICATION

These results demonstrate the potential importance of envelope information for auditory

classification of brief sounds. The results are consistent with a narrowband analysis of

envelope information and the primary importance of modulation rates less than 200 Hz.

The results suggest that good identification of brief signals can be achieved with a large

reduction in the effective bandwidth of signals by using relatively low modulation rates

in a small number of bands, simplifying the problem of automatic classification.

ADMINISTRATIVE INFORMATION

This investigation was conducted under Office of Naval Research Work Unit 61153NRR04209.001-ONR4424207. The views expressed in this report are those of the authors

and do not reflect the official policy or position of the Department of the Navy, Department of Defense, or the U. S. Government. It was submitted for review on 29 October

1990, approved for publication on 12 July 1991, and has been designated as Naval Submarine Medical Research Laboratory Report No. 1171.

ii
ABSTRACT

Auditory classification of a set of brief sounds was compared to that in a number of conditions that manipulated the spectral and temporal information in the signal. Multidimensional

scaling techniques identified the use of six perceptual dimensions that could be accounted for by

amplitude-envelopes of critical-band filtered signals. Modulation rates above 200 Hz did not

contribute much to classification although there was some suggestion that rates greater than 200

Hz were significant for one of the dimensions. These results indicate the potential importance of

envelope information for auditory classification of brief sounds.

iii
Narrowband and Broadband Envelope Cues for Aural Classification

INTRODUCTION

A signal's amplitude-time variation, or

envelope, contains nonspectral information

that can be used by the auditory system to

identify that signal. Although there is uncertainty about the mechanisms that underlie the

auditory system's processing of envelope

information, it is typically assumed that the

signal is filtered, and then subjected to a nonlinearity such as a full-wave or half-wave

rectification. Additionally, the system's

limited ability to follow rapid fluctuations in

the resulting signal is described by a central

integrator with a time constant.

Such a model can be applied to data for

modulation-rate discrimination, modulation

detection, and auditory classification, but

there is no consistent bandwidth estimate for

the initial filter across these tasks. Studies by

Buus (1983) and Hanna (1989, 1991) indicate

that modulation rate discrimination, where the

listener was asked to identify the faster of two

modulation rates, show limitations due to

relatively narrow (roughly one-third octave)

critical-band filtering. In contrast, studies of

modulation detection (e.g., Viemeister, 1979;

Formby & Muir, 1988) produce bandwidth estimates broader than critical bandwidths.

Studies of auditory classification by Van

Tassell, Soli, Kirby, & Widin (1987) and

Hanna (1990) are equivocal regarding filter

bandwidth. They found that the broadband

envelope contained sufficient information to

convey features of complex signals, supporting the notion of broad initial filtering prior to

envelope extraction by the auditory system.

However, since Van Tassell, et al. and Hanna

never filtered their signals prior to envelope

extraction, it is unclear what role critical band

filtering may have played in extracting envelope information. If the same modulation

pattern was present in each band then the

broadband envelope would be the same as

those obtained from critical band filtering. In

this case, one would expect that the broadband envelope would provide the information

needed for classification even though the

auditory system is using the narrowband

envelopes. On the other hand, if the modulation was different in each band the broadband

modulation would not necessarily preserve

the perceptual information present in each

band. The present study examines classification of the complex signals used by Hanna

(1990), but includes conditions with stimulus

bandwidths comparable to critical bands.

A second issue concerning the use of

envelope cues in classification is the nature of

limitations imposed by post-filtering integration. An integration time constant of 2-3

msec provides good descriptions of the data

from many experiments. This value suggests

that envelope rates greater than 50-80 Hz

would be attenuated by post-filtering temporal

integration. These effects are generally

observed in studies of modulation detection

and rate discrimination in noise. However,

Buus (1983) found that for high-frequency

two-tone complexes, modulation-rate discrimination was relatively unaffected up to

rates of 640 Hz. Van Tassell, et al. (1987)

suggested that modulation rates above 200 Hz

are perceptually significant for classification

of speech sounds. In the present study, the

envelope is low-pass filtered at several frequencies to determine whether higher frequencies

I
contribute significantly to auditory classification of complex nonspeech sounds.

METHOD

Signal conditions. Twenty-four one-second

stimuli were extracted from digitized recordings of underwater sounds. Each stimulus contained an acoustic event with duration ranging

from tens to hundreds of milliseconds. These

twenty-four signals represented three exemplars

from each of eight categories of underwater

events. The recordings had been digitized at a

12.5 kHz sampling rate with 12 bits of linear

encoding of amplitude.

Subjects were tested on their ability to

classify the signals into the eight categories

under eleven conditions. In condition 1, listeners classified the original signals. In condition 2 the stimuli were band-pass filtered from

2200 to 2800 Hz; in condition 3, the original

signals were band-pass filtered from 710 to

900 Hz. The envelopes of the 2200-2800 Hz

band-pass filtered signals (i.e., the envelopes

from condition 2) were used to generate

stimuli for conditions 4, 5, and 6. In condition 4, the envelopes modulated a 2500-Hz

carrier. In condition 5, the envelopes were

low-pass filtered at 100 Hz prior to modulating the 2500-Hz carrier. In condition 6, the

envelope was low-pass filtered at 10 Hz prior

to modulating the 2500-Hz carrier. In condition 7, an 800 Hz carrier was modulated by

the envelope of the 710-900 Hz band-pass

filtered signals (i.e., the envelopes from condition 3). The envelopes of the original signals

(condition 1) were used to generate stimuli in

conditions 8, 9 and 10. In condition 8, the

envelopes were low-pass filtered at 1 kHz

prior to modulating a 2500-Hz carrier. In

condition 9, the envelopes were filtered at 100

Hz prior to modulating a 2500-Hz carrier. In

condition 10, the envelopes were filtered at 10

Hz prior to modulating a 2500-Hz carrier. In

condition 11, the envelope of the original

sigrlal was simply used as a time waveform.

Signal enerti. In conditions 1-3, the

original set of digitized stimuli were presented

over 16-bit digital-to-analog converters with a

12.5-kHz sampling rate. Stimuli were bandpassed filtered from 2200 to 2800 Hz (condition 2) or 710-900 Hz (condition 3) using a

Wavetek filter (model 753A, asymptotic

rejection rate of 115 dB/octave).

Envelopes of stimuli from conditions 1-3

were generated using the Interactive Lab

System (ILS) from Signal Technology, Inc.

The envelopes were presented over 16-bit

digital-to-analog converters and low-pass

filtered at 5 kHz. The carriers were generated

by a Krohn-Hite oscillator (model 4180). The

carrier was multiplied by the envelope and

low-pass filtered at 5.0 kHz. In conditions

requiring filtering of the envelope, the

digitized envelopes were convolved with an

exponential function (e at, t > 0) with decay

constant chosen to produce the desired lowpass filter cutoff of 10, 100, or 1000 Hz (3-dB

down points). The filter defined by the exponential function has an asymptotic rejection

rate of 6 dB/oct.

In all conditions, a programmable attenuator

was used to adjust the amplitude of each

signal to a comfortable listening level. In

addition, on each trial, stimulus levels were

randomized over a 15-dB range to minimize

the use of amplitude as a classification cue.

An electronic switch gated the stimuli with

20-msec sine-squared ramping. Stimuli were

presented to the right earphone of a

Sennheiser HD430 headset.

Procedure. Initial training was conducted

with reduced signal sets to facilitate the

2
learning of the category labels. Blocks of trials using exemplars from categories one

through four were run followed by blocks

using exemplars from categories five through

eight. On each trial, one stimulus from the

original set was presented and the listener classified it into one of four categories. Feedback

was given on each trial by displaying the correct response on the screen. Listeners had

720 trials by which time they were performing quite well (approximately 85% correct)

with these reduced signal sets.

After initial training, data were collected

over a three day period for each condition.

Day one was a familiarization session and

these data were not used in the analyses.

Days 2 and 3 were testing days for each condition. Each of the twenty-four stimuli were

presented twice within each block of fortyeight trials. Eighteen blocks of trials were run

each day. Feedback was given on each trial by

displaying the correct response on the screen.

1.00

Iw

40

09I0.801-

0.601-

0.401-

0.201-

0.00

All listeners were tested simultaneously which

prevented counterbalancing the conditions

across listeners.

Listeners. Three paid volunteers served as

listeners. Each had normal hearing sensitivity

(less than 15 dB HL at octave frequencies

from 250 to 8000 Hz). Two of the subjects

had participated in a previous experiment

using similar stimuli. The third subject had

never heard these sounds prior to this experiment.

RESULTS & DISCUSSION

Figure 1 shows the proportion correct in

each of the eleven conditions averaged across

listeners. A repeated-measures analysis of

variance indicated a significant effect of condition (p.<001).

Critical-band information. Performance on

the original signals (condition 1) was quite

I 2 3 4 5 6 7 8 9 10 II

CONDITION

Figure 1. Proportion correct, averaged across the three listeners, for the eleven

conditions. Error bars represent standard deviations across the three listeners.

3

I I I I I I I I I I I

MI IJ I Iw I ITI Ih w I I
good (94%). Proportions correct on the filtered

signals of conditions 2 and 3 were significantly

different than condition 1. Filtering the signals

from 2200-2800 Hz (condition 2) decreased

performance to 71% (p.<001); filtering from

710-900 Hz (condition 3) decreased performance to 68% (p=.002). The conditions that

used the envelopes of the signals from these

two conditions as modulators (conditions 4

and 7) did not produce a significant difference

in proportions correct compared with that on

the corresponding filtered signals (73% and

67%, respectively), suggesting that the envelope

adequately represents the perceptual information within each critical band. Filtering the

envelope of the high-frequency band at 100

Hz prior to modulation of the carrier (condition 5) also had little effect on performance

(67%) compared with the unfiltered envelope

condition (p.>05). Filtering the envelope at

10 Hz (condition 6) did produce a significant

decrease to 44% (p=.008). Given the shape of

the filters used to filter the envelope, these

results suggest that envelope frequencies

above 200 Hz were not perceptually important

for the high-frequency-band filtered signals.

However, perceptually important information

did exist between 20 and 200 Hz and below

20 Hz.

Broadband information. Using the broadband envelope, filtered at 1 kHz (condition 8),

decreased performance to 82%, which was

significantly different than that with the

original signals (p=.007). Although all three

listeners showed progressively lower scores as

the envelope was filtered at 100 Hz (64%) and

at 10 Hz (46%), conditions 9 and 10, respectively, these successive comparisons were not

statistically significant. Nonetheless, the size

of these effects and their consistency across

subjects suggest that modulation rates greater

than 200 Hz, from 20-200 Hz, and less than

20 Hz are used for classifying these signals.

Listeners' performance in the condition

with the broadband envelope filtered at 100

Hz was similar to that for conditions that used

the envelopes of the 710-900 Hz and 2200-

2800 Hz bands (64% vs. 67% for both conditions 5 and 7). Also, filtering the envelope at

10 Hz had a similar effect whether the envelope

came from the broadband signal or the signal

filtered from 2200-2800 Hz (46% vs. 44%).

This similarity in performance across conditions that used different filtering suggests that

the broadband envelope may simply reflect

signal features that are present in narrower

bands. The similarity of features present in

each of these conditions will be explored

further in the next section by examining the

pattern of errors made in each of these conditions. A finding that similar errors are made

in each condition would support the conclusion

that these signals have similar modulation

patterns in each frequency band and that the

apparent efficacy of the broadband envelope

derives from its similarity to the narrowband

envelopes. The finding of different patterns of

errors across conditions would indicate the

use of different cues in these conditions that

may or may not correspond to the cues used

to classify the original unaltered signals. In

this latter case, the similarity in overall performance would indicate that the broadband

envelope conditions were not fully conveying

the narrowband cues, since then the broadband conditions should be better than comparable narrowband conditions.

The consistent, but statistically nonsignificant, decrease in performance when broadband signal envelopes were filtered at 100 Hz,

leaves open the possibility that envelope

fluctuations greater than 200 Hz play a role

for classification of these sounds.

The condition where the broadband envelope

was played as a time waveform (condition 11)

4
yielded 93% correct, which was not significantly

different than performance with the original

signals. It is curious, and perhaps suspicious,

that the envelope by itself (condition 11) can

be classified as well as the original signals. In

fact, the envelope by itself sounds remarkably

similar to the original signals. This result

would suggest that the envelope contains all

of the information needed to classify these

signals. However, filtering the envelope at 1

kHz and using it to modulate a tonal carrier

(condition 8) resulted in significantly poorer

performance, implying that envelope frequencies above 1 kHz contain usable envelope

information. Such an upper limit exceeds that

suggested anywhere. Examination of the

broadband envelope led to another possible

explanation - the envelope begins to resemble

a full-wave rectification of the signal. The

broadband envelope thus begins to follow the

fine structure of the waveform and may be

providing spectral cues from the signal.

Multidimensional scaling. The data were

examined in greater detail using the patterns

of errors. Conditions that yield similar percents

correct (e.g., conditions 2, 3, 4, 5, 7, and 9)

may nonetheless have quite different signal

features. This would be supported by finding

different patterns of errors across conditions.

Conversely, if the signal features are similar

across conditions, then the patterns of errors

should also be similar.

Multidimensional scaling (MDS) techniques were used to simplify the analyses of

error patterns. This analysis uses a measure

of similarity between signal pairs to determine

a multidimensional stimulus representation.

For the present study, the measure of

similarity was defined as:

8

s(ij) = I p(i,k)p(j,k) i=1,24 j=1,24 (1)

k=l

where p(i,k) is the probability that stimulus

j will be called category k. For a given pair of

signals, this number is the probability that the

two signals would be given the same category

label assuming independent responses to each.

A similarity matrix (lower half, diagonal

absent) was computed for each of the three

listeners in each of the eleven conditions. The

SINDSCAL procedure (Carroll & Chang,

1970; Kruskal & Wish, 1978) was used to

scale the 33 matrices (3 subjects x 11 conditions). This technique produces a single multidimensional representation of the 24 signals.

Each dimension in the signal space is taken to

represent a stimulus feature that distinguishes

the signals from each other. Within the

SINDSCAL analysis, the similarity of two

signals is predicted by Euclidean distance of

signals in the multidimensional space. Differences across the 33 similarity matrices are

accounted for by a weighting vector for each

of the 33 matrices that gives different weights

to each of the dimensions. The weighting

vectors reflect the fact that these dimensions

may be present to varying degree for individual

listeners or in the different stimulus conditions. Conditions (or listeners) with different

patterns of errors would indicate the use of different stimulus features and therefore different

weighting vectors. A low weight given to a

dimension would suggest the loss of a significant stimulus feature resulting from the

signal manipulation used for that condition.

Thus the MDS results can be used to make

comparisons across conditions to determine

whether common features are present in each.

SINDSCAL representations were generated for eight dimensions and less. Variance

5
accounted for (VAF) by each solution was

compared to determine the appropriate dimensionality. Starting from two dimensions,

VAF increased by 7-11% with each added

dimension up to six. Inclusion of additional

dimensions increased VAF by only 2-3%.

Thus, a six-dimensional solution, accounting

for 80% of the variance, was used for further

analyses. This solution uses 342 parameters

(3 subjects x 11 conditions x 6 dimension

weights + 24 stimuli x 6 dimension values) to

account for 6336 data values (3 subjects x 11

CONDITION

oz-;

04-I

6g

I-,

LU

CJ

LL.

LU0

r.D

z

I-I

:=

I-4

LU:3

0.6

0.5

0.4

0.3

0.2

0.1

0.0

conditions x 24 stimuli x 8 response categories).

Weight vectors were generally similar across

listeners (average s.d. = .03), so results were

averaged across listeners to simplify further

analyses.

MDS Analysis of Narrowband Conditions.

Figure 2 shows the weight vector coefficients

for the original signals (condition 1, shown as

triangles) and the four conditions derived

from the 2200-2800 Hz filtered condition

(condition 2, squares; condition 4, circles;

ORIGINAL SIGNALS

2.2-2.8 KHz FILTER BAND

ENVELOPE (UNFILTERED)

ENVELOPE (FILTERED AT 100 Hz)

ENVELOPE (FILTERED AT 10 Hz)

2 3 4 5 6

MDS DIMENSION NO.

Figure 2. Weighting coefficients, averaged across listeners, for the six dimensions

obtained from the SINDSCAL analysis. The parameter is the stimulis condition -

condition 1 A, condition 2 , condition 4 0, condition 5 V, and condition 6 0.

6

- o~

I I I
condition 5, downward triangles; and condition 6, diamonds). For the original signals,

the weights are roughly equal across all six

dimensions. In the other four conditions, two

clear effects are observed. First, a very low

weight is given to Dimension 3 (D3) for all,

indicating that the 2200-2800 Hz band did not

convey the signal feature associated with D3.

Second, the weights for D4, D5, and D6 are

relatively unaffected by low-pass filtering the

envelope at 100 Hz (condition 5), but are

greatly reduced when the envelope is filtered

at 10 Hz (condition 6). This suggests that the

signal features associated with these dimensions (D4, D5, and D6) are conveyed by

modulation rates in the general range from

20-200 Hz. D 1 and D2, which receive slightly greater emphasis as the other features are

removed, are still present with only low

modulation rates in the signals (less than 20

Hz). Moreover, it should be noted that the

filtered band stimuli (condition 2) produce

very similar weights as stimuli generated from

the envelope of that band (condition 4). The

differences in dimension weightings across

conditions 1, 2, 4, 5, and 6 correspond well to

the changes found in proportion correct

shown in Fig. 1 in that conditions that are not

significantly different in percent correct also

show similar dimension weights and conditions that are significantly different in percent

correct have different weights on at least one

dimension.

CONDITION

A 1 - ORIGINAL SIGNALS O"1 3 - 710-900 Hz BAND

o 7 - ENVELOPE (UNFILTERED)

0.6

I.- z

U.

C-,

b-4

Li.,

L,_

W

3,_

I-I

==

I,-4

LU

0.51-

0.41-

0.31-

0.21-

0. 1 1-

0.0

I I I I I I

1 2 3 4 5 6

MDS DIMENSION NO.

Figure 3. Weighting coefficients, averaged across listeners, for the six dimensions

obtained from the SINDSCAL analysis. The parameter is the stimulus condition - condition 1 A, condition 3 [1 and condition 70.

7

I I I I I I
Figure 3 shows the weight vector coefficients for the original signals (condition 1,

triangles) and the two conditions derived from

the 710-900 Hz filtered condition (condition

3, squares; and condition 7, circles). Compared

with the relatively equal weighting across

dimensions for the original signals, the

710-900 Hz filtered signals show a stronger

emphasis for D3 and a low weight for D5 and

D6. The weights are very similar for filtered

signals (condition 3) and stimuli generated

from the envelope of that band (condition 7).

Figures 1, 2, and 3 taken together suggest

some conclusions. Stimuli filtered to a critical

bandwidth are classified in a very similar way

as stimuli created by modulating a tone by the

envelope of that filtered band. Thus, the

envelope of critical band signals conveys

much of the perceptual information of that

signal. All six dimensions are present in at

least one of the critical-band envelope conditions. D1, D2, and D4 are envelope features

that are present in both a high-frequency and a

low-frequency band and thus may be considered

to be present broadband. D3 is an envelope

feature that is only present in the low band

and D5 and D6 are envelope features that are

only present in the high band. Furthermore,

percents correct (Fig. 1) and dimension

weights (Fig. 2) were unaffected by low-pass

filtering the envelope at 100 Hz (condition 5).

It appears that classification can be accounted

for by narrowband envelope cues less than

200 Hz.

MDS Analyses of the Broadband Conditions. Figure 4 shows the weight vector coefficients for the original signals (condition 1,

triangles) and three conditions derived from

the broadband envelope (condition 8, squares;

condition 9, circles; and condition 10, downward triangles). Condition 8, which used the

broadband envelope filtered at 1 kHz to

modulate a 2500 Hz tone, contained all six

dimensions, but to varying degrees. D1, D2,

and D4 had slightly higher weights than for

the original signals. This result is consistent

with the finding that these three dimensions

were envelope features that are probably

present in each of several critical bands.

Therefore it is expected that this information

should be clearly present in the broadband

envelope. On the other hand, D3, D5, and D6

were present in only one of the two bands

studied. The strength of these features would

be lessened in a broadband envelope. In fact

the weights shown in Figure 4 support such a

view because the weights for condition 8 are

less than for the original signals. These

dimensions, although reduced in weight, are

still present to a significant degree, which

may account for the relatively good performance in this condition (82% correct) - since

both low-band and high-band features are

available performance is expected to be better

than the narrowband condition.

The reduced strength of D3, D5, and D6 in

the broadband envelope condition would also

explain the finding that performance found in

condition 8, although high, is still significantly poorer than for the original signals. Since

all six dimensions are represented in the

broadband condition, one must assume that

some of them are not as strong otherwise

performance would be as good as for the

original signals. Furthermore, the fact that

performance when the broadband envelope

was filtered at 100 Hz (condition 9) was no

better than the narrowband envelope conditions with comparable limits on modulation

rate (conditions 5 and 7) also suggests that the

distinct cues present in the narrowband

envelopes are not as clearly perceptible as in

the broadband envelope. The results of Fig. 4

are also generally consistent with those for

conditions 8, 9, and 10 of Fig. 1. The small

8
but consistent changes in percent correct

shown in Fig. 1 are accompanied by only

slight changes in a single dimension in Fig. 4.

These results are in contrast to those for the

narrowband condition, where larger and statistically significant changes in percent correct

are associated with more pronounced changes

in dimension weights. Thus alterations of the

broadband envelope are more weakly related

to the perceptual dimensions than are changes

in the narrowband envelope. For these

reasons, and given the finding that the weights

of D3, D5, and D6 were higher in the narrowband envelope conditions than in the broadband envelope conditions and more closely

resembled the weights for the original signals,

it is probable that the auditory system is

normally using separate envelope information

from a number of bands in spite of the good

performance observed using the broadband envelope.

Figure 4 also shows that D3 is still present

even with envelope filtering at 10 Hz (condition 10) suggesting that this is a low-modulationrate (less than 20 Hz) cue present at lower

spectral frequencies. D4, D5, and D6 are all

relatively reduced with filtering of the envelope

at 10 Hz, which agrees for the most part with

the results with the 2200-2800 Hz band (Fig.

2). For D5, the filtering effect is not as

pronounced for broadband envelope (Fig. 4)

as for the high-frequency-band envelope

CONDITION

1 - ORIGINAL SIGNALS

8 - ENVELOPE (FILTERED AT 1 KHz)

9 ENVELOPE (FILTERED AT 100 Hz)

?10 - ENVELOPE (FILTERED AT 10 Hz)

0.6

I--

LUJ -,4

Cm,,

LL.

LU

0

2C-

-4I.-

==

-,4

LUJ 3

0.5

0.4

0.3

0.2

0.1

0.0

I 2 3 4 5 6

MDS DIMENSION NO.

Figure 4. Weighting coefficients, averaged across listeners, for the six dimensions

obtained from the SINDSCAL analysis. The parameter is the stimulus condition -

condition 1 A, condition 8 0 condition 9 0, and condition 10 V.

9
(Fig. 2). For D6, the main reduction is observed as the envelope filter is changed from

1 kHz (condition 8) to 100 Hz (condition 9).

This result may indicate a high-modulationrate cue that was not observed in the 2200-

2800 Hz conditions because this band was

not sufficiently broad to support that rate of

modulation. Additional conditions with somewhat broader bands or bands that more closely resemble auditory filters, which do not

have the extremely sharp cutoffs used in thee

present study, could determine whether these

modulation rates play a significant role.

The weights for condition 11, which used

the broadband envelopes as stimuli, were very

similar to those for the original signals. As

already stated, this result may reflect the carryover of spectral information to the broadband

envelope.

Implications for automatic classification.

The finding that eight stimulus categories can

be described by six perceptual dimensions or

features does not seem like a parsimonious

description of the data. However, one must

keep in mind that these dimensions are

describing 1. sets of modified stimuli. From

the dimension weights we can associate

specific perceptual features with the different

acoustic information present in each stimulus

set. Thus, each feature can be related to a

range of modulation rates present in a specific

frequency band (or bands). Of the six dimensions, D1, D2, and D3 depend on very low

modulation rates (<20 Hz), whereas D4, D5,

and D6 use intermediate rates (20-200 Hz).

D3 stems from modulation patterns present at

lower spectral frequencies, D5 and D6 from

modulation patterns present at higher spectral

frequencies, and D 1, D2, and D4 from

modulation patterns that are present across a

broadband of frequencies. The training of

automatic classification algorithms based on

this specific acoustic information would be more

successful than those based on the original

signals for two reasons. First, algorithm input

based on the specific acoustic information has

a much reduced bandwidth compared with the

original signals (20-200 Hz vs 5000 Hz),

which improves the algorithm's performance.

Second, the relevant features should be more

distinct in the modified stimuli thus making it

easier for the algorithm to distinguish the

category features.

SUMMARY

This study provides a more detailed

analysis of the importance of envelope features

for aural classification than previously

reported by Van Tassell, et al. (1987) and

Hanna (1990). These two previous studies

found evidence that the broadband envelope

conveys important perceptual features. The

present study found, for the brief sounds used

here, that envelope features accounted for all

of the features identified. In particular,

classification performance, as measured by

percent correct and the results of multidimensional scaling, show no difference between

conditions with third-octave-band filtering and

corresponding conditions using the envelope of

these filtered bands to modulate a tonal carrier.

Although the results are not definitive, the

classification features were more clearly associated with the envelopes of critical-band

filtered stimuli than of the broadband stimuli.

These features were well accounted for by

modulation rates less than 200 Hz, although

there was some suggestion that rates greater

than 200 Hz were significant for one of the

features.

10
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,

Psvchometrika 3,1283-319.

Formby, C., & Muir, K. (1988). Modulation

and gap detection for broadband and filtered noise signals, Journal of the Acoustical Society of America 84, 545-550.

Hanna, T. E. (1989). Modulation-rate

perception: Identification and discrimination of modulation rate using a noise

carrier, Naval Submarine Medical

Research Laboratory Technical Report No.

1128.

Hanna, T. E. (1990). Contributions of envelope information to classification of brief

sounds, Naval Submarine Medical Research

Laboratory Technical Report No. 1165.

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Van Tassell, D. J., Soli, S. D., Kirby, V. M.,

& Widin, G. P. (1987). Speech

waveform envelope cues for consonant

recognition, Journal pf the Acoustical

Society f America L2, 1152-1161.

Viemeister, N. F. (1979). Temporal modulation transfer functions based upon modulation thresholds, Journal of the Acoustical

Society of America 66, 1364-1380.

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161153N 42 1RR 04209 RRO420901 IR&TA2A4207

11. TITLE (Include Security Classification)

(U) Narrowband and Broadband Envelope Cues for Aural Classification

12. PERSONAL AUTHOR(S)

-Thomas• F.- Tnnnn pnd YVAnnn,- P Mnnr, T.TQ,.r4

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FROM _____TO ___19 JUL 12 14

16. SUPPLEMENTARY NOTATION

17. COSATI CODES 18. SUBJECT TERMS (Continue on reverse 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 hecessary and identify by block number)

Auditory classification of a set of brief sounds was compared to that in a number of

conditions that manipulated the spectral and temporal information in the signal.

Multidimensional scaling techniques identified the use of six perceptual dimensions

that could be accounted for by amplitude-envelopes of critical-band filtered signals.

Modulation rates above 200 Hz did not contribute much to classification although there

was some suggestion that rates greater than 200 Hz were significant for one of the

dimensions. These results indicate the potential importance of envelope information

for auditory classification of brief sounds.

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John J. O'Hare (2(2'w c6-49- nI Code 1142PS

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