Identification of random auditory waveforms Irwin Pollack Mental Health ResearchInstitute, Universityof Michigan,Ann Arbor, Michigan 48104 (Received11 February1975;revised8 August1975)

Listeners quicklylearnto identify,apparently on an absolute basis,theorderingof a pairof sounds, where onesoundis a specificrandomselectionwhichis constantoversuccessive observations, and wherethe other soundvariesover successive observations. The accuracyof identificationis not directlyrelatedto the uncertaintyof the poolof possible waveforms. A widerangeof sampledurationsand spectracharacterize the identifiablepools.Increasingthe predictabilityof the sequences doesnot improveidentification accuracy.Listenersalsocan identifyoneof two selections from the samepool and can identifydepartures from a prototypewhichtheyhaveneverheard.Sinceall randomselections from the samepoolhavenearly identicallong-termaveragespectra,it is concludedthat the listenermustperforma short-term,or running spectrumanalysisupon the signals. SubjectClassification:65.22, 65.75, 65.68.

INTRODUCTION

Several procedures have been directed toward whether random auditory waveforms randomly selected from a defined pool of waveforms are equally-effective. For

example, Watson (1964) and Ahumadaand Lovell (1970), employing random noise in a signal detection task, demonstrated that the masking effectiveness of individual random noise samples was related to the noise density

in the vicinity of the signal frequency. Green (1964) examined the consistency of detection judgments over successive replications of recorded noise samples, and found performance differences among different

samples. Pfafflin and Mathews (1966) and Pfafflin (1968) employed a fixed set of 12 noises and also demonstrated that the masking effectiveness was related to the noise density in the vicinity of the signal. The latter studies also suggested that listeners may learn specific features about the random selections. Pfafflin and Mathews had their listeners identify the 12 noise waveforms. Identification scores of 50% correct were achieved in about 100-150 trials per signal. More

importantly, some waveforms yielded scores just above chance and some yielded nearly perfect identification. Pfafflin

examined

detection

scores

when

the 12 noises

were intermixed within a single session and when each of the noises

was

tested

alone

in an entire

session.

Some noises, but not all, showed tremendous improvements under the latter procedure. Variation in the overall level of the signals did not reduce the effectiveness of the latter procedure. Clearly, specific features of the waveform

could be mastered

to assist

detection

performance.

Indirectly, Guttmanand Julesz (1963) also demonstrated

that

individual

random

selections

from

a de-

fined source can be identified. Their signals consisted of either different random waveforms successively connected, or of repetitions of individual random waveforms. Repetitions of random waveforms up to 0.5-1 sec in duration were easily detected; and with effort, repetitions of random waveforms up to 4 sec duration were detectable. Such detection is not based upon local amplitude peaks, since repeated constant-amplitude ran-

dom pulse patterns can also be detected(Pollack, 1971). 1262

J. Acoust.Soc. Am., Vol. 58, No. 6, December1975

The present paper is concerned with the identification of specific random waveforms presented on different

occasions(long-term auditory memory?), rather than the detection of repetitions of specific random wave-

forms within a single presentation (short-term auditory memory?). Specifically, we shall be concerned with

the characteristics

of the sources

of identifiable

randomly selected signals. A previous study examined the characteristics of sources of signals in which

within-presentation repetitions were detectable (Pollack, •2). I. POLARITY

CODING

A. Approach 1. Outline

A method is first described which generated randomly selected, finite-state sequences from very large information pools. A method is next described for translating these sequences into the temporal microstructure of auditory signals. And, finally, an experimental procedure is described for identifying specific random signals which were unchanged from observation to observation.

2. Finite-state random sequences Pseudorandom number sequences were generated

algorithmically by a PDP-9 (Digital Equipment Corporation) computer. When the algorithm was initialized by the same number, the same pseudorandom number sequence was generated. When the algorithm was initiated by a different number, a different pseudorandom number sequence was generated. Sequences of

numberswere convertedto sequencesof 0's and 1's in terms of the probability

of one of the states or in

terms of the sequential repetition probability (SRP)of repeating the previous state. The 0's and l's were then converted to + and - polarities of a polarity-modulated pulse train. The time between successive pulses was constant and is called the interpulse interval or IPI. For example, the random sequence 001... at an interpulse interval of 0.5 msec would translate to + pulse, wait of 0.5 msec, + pulse, wait of 0.5 msec, - pulse, .... Copyright(D 1976 by the AcousticalSocietyof America

1262

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1263

I. Pollack:Randomwaveformidentification

1263

A sequential repetition probability SttP of 0.50 is associated

with a chance distribution

of successive

polarities; an SttP of 1.0 is associatedwith a mono-

polar pulsepulse train with a fundamentalperiod equal to the interpulse interval IPI; and an SttP of 0 is associated with a sequence of alternating polarity with a fundamental period of twice the interpulse interval. Consequently, the spectrum of a polarity modulated signal becomes successively narrower as the SttP is varied

from

0.50

toward

1.0 or toward

zero.

At short interpulse intervals, the signals sound like a wide-band random noisewith extremely subtle changes

in timbre, presumably as a result of the processing of runs of identical or of alternating polarity (Cramer and Licklider, 1957). It is important to note that the individually coded elements--here

single pulses of + or -

polarit'y--are not separately perceived. This feature contrasts sharply with a large group of other studies which have examined the short-term

auditory memory

for sequences of individually perceived tonal elements

(e.g., Deutsch, 1972; Divenyi and Hirsh, 1974; Dowling, 1971; Elliott 1970; Harwood, .1973; Preusser, 1972; v. Noorden, 1975; Warren, 1974; Watson el al., 1975; Wickelgren, .1969). The information in the present signals was encodedwithin the temporal microstructure of the signals, rather than in terms of discretely perceived units. The qualitative changesand possible processing mechanisms associated with modifications of the temporal microstructure and those associated with longer tonal signals have been discussed by several authors, e.g., Hirsh, 1959, and Divenyi and Hirsh, 1974, especially in conjunctionwith the minimum auditory integration time, e.g., Green, 1973; Patterson and Green, 1970.

4. Experimental conditions Experimental conditions differed with respect to the number of pulses, n, and the interpulse interval of the

sequences IPI. A trial of 40 obseryations represented a single experimental condition in contrasting one of two paired orders. A total of 159 trials was employed, but we shall consider only the results of 68 different conditions without interference plus 19 replications of a reference condition scattered throughout the testing program. The specific parameters for the reference condition were n=400 pulses, SRP=O. 50, and IPI=O. 5 msec. Each of eight listeners heard the entire set of 159 trials upon two separate occasions, for a total of

about l0 s observations. Unless specified otherwise, the parameters associated with the reference conditions were employed. The sound level was about 55 dB above

threshold. The electrical pulses were brief (10 •sec) before smoothingby binaural earphones(Koss PRO-4). The listeners were university music majors who had previously participated in auditory psychophysical tests. Within this highly selected group, performance was unrelated to the duration of their experience within formal psychophysical tests. B. Results

1. Performance upon the very first trial The listeners quickly responded to the task requirements. The average performance upon the very first

trial to the reference conditionwas 83%, 89%, 94%, and 91% correct, for the first four blocks of ten observations each. Thus, we are not considering extremely subtle, obscure features of auditory signal processing requiring extremely long periods of train-

ing, as consideredby Tanner and Rivette (1967). 2. Sourcesof variation in identification performance

3. Procedure A trial

blocks

Table I lists some of the factors influencing the ac-

consisted

of 40 observations--four

of ten observations

parameters.

each--with

successive

a fixed

set of

Upon each observation, two signals were

presented: a specific or constant(C) random sequence which did not change over the entire trial and a variable (V) random sequencewhich changed upon each new observation.

reference sequencesranged from 86% to 98% correct TABLE

I.

Sources of variation in identification

The order of presentation was either

constant-then-variable

(V-C).

curacy of identification for 18 of the reference signals (excepting the very first presentation) and for the first 100 sequences. The identification scores for the 18

A. Reference

(C-V) or variable-then-constant

seq ue nces

The task of the listener was to identify the

order of presentation by pressing one of two response buttons. Feedback was given after each response.

Block

Only chance response is possible on the first observation of each trial. The percentage of correct observations is expressed relative to 9.5 observations on the first

block

and relative

to ten observations

on

Listeners

the remaining blocks. The within-pair delay was 0.5 sec; the time between successive pairs v•as the reaction time to the preceeding pair plus 1.0 sec. The listener's task was not to decide whether the two signals within a pair were the same or different. The two signals were always different from each other. Rather, the task was to decide the order of two signals, one of which was constant from observation to observation; and one of which

varied

from

observation

Order

accuracy. B. First

100

s eq ue nces

(%)

(%)

i 2 3

94.9 93.6 93.9

85.7 85.1 86.1

4

93.8

85.8

i 2

92.2

85.5

98.8

93.1

3

94. 9

86.0

4 5

92.9 97.3

83.9 90.3

6 7 8

90.2 93.2 92.7

79.2 82.7 84.6

i 2

92.8 95.3

84.0 87.3

to observation.

J. Acoust. Soc. Am., Vol. 58, No. 6, December 1975

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1264

I. Pollack: Random waveform identification

1264

&-•

identifications (median: 94.5%, with 89%of cases be-

vations. Since almost all of the other experimental conditions were associated with only a single sequence,

I

12 '

i

50 '

i

200 '

I

3200

i

ß

ß

[]

[]

z

o

800 '

'

1

PULSE TRRIN RETENTION

lOO

ß

90

some of the "noise" in the experimental relations is not removable by simply adding additional listeners or ad-

n- 8o

diti onal

o

observations.

MESSAGE DURATION IN MSEC

3

.75

tween 91% and 97% correct). This variability is presumably related to the characteristics of the particular sequences, rather than to a limited number of obser-

$ 70

Differences in performance within the four blocks of ten observations are small. Stated differently, the skill of identifying specific random selections is rel-

0

6o 5o

atively insensitive to "short-term" learning effects. There are substantial differences

[]

among listeners.

I • .50I • 2I i 8I i 32I , 128I , 5 ;2

.12

There is, however, some evidencefor "long-term"

E]-,-{2]

learning in that scores under the second presentation of each condition are slightly, but consistently, higher than under the first ordering of that condition.

INTERPULSE INTERVAL IN MSEC

FIG. 1. Accuracy of identification of specific random selections for polarity-modulated pulse trains as a function of the in-

terpulse interval (opensquares and lower abscissa) and as a function of the duration of the message (filled triangles and upper

3. Accuracy/'elated to the uncertainty of the select/on pool

abscissa). The latter function is restricted to IPI-