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DETECTION OF SIGNALS IN WHITE NOISE

By

Paul Steele Niswander

A THESIS

Submitted to
Michigan State University
in partial fulfillment of the requirements
for the degree of

MASTER OF ARTS

Department of Speech

1964

 

TABLE OF CONTENTS

LIST OF TABLES . . . . . . . . . . . .
LIST OF FIGURES. o 9 g o o e o o o o 0 0
LIST OF APPENDICES. n o o o o o o o o o 0
Chapter _
I. INTRODUCTION . . . . . . . . .
Background. . . . . . . . .
Statement of the Problem . . . . . .
Organization of the Thesis . . . .

II. REVIEW OF THE LITERATURE. . . . . .

Background .. .
Studies Related to Present Experimental
Design . . . .

Classical Psychophysical Methods

III. PROCEDURES AND EQUIPMENT. . .
Subjects . . . . . . . . . . .
Procedures. . . . . . . . . . .
Equipment . . . . . . .

IV. RESULTS AND ANALYSIS OF DATA

Data Reduction .
Results .
Statistical Analysis

V. SUMMARY, CONCLUSIONS, AND IMPLICATIONS FOR
FURTHER RESEARCH. . . . . . . .

Summary and Conclusions . .
Implications for Further Research .

BIBLIOGRAPHY. . . . . . . . . . . . . .
APPENDICES . . .
ii

Page
iii
iv

”3

as
us

48
52

LIST OF TABLES

Table Page
1. Pure-Tone Signal Intensity Ranges . . . . 23
2. Per Cent Detection Data . . . . . . . 32
3. Analysis of Variance Summary Table. . . . Al
A. Analysis of Variance Summary Table. . . . 41

iii

LIST OF FIGURES

Figure Page
1. White Noise Power Spectrum . . . . . . A
2. Distorted White Noise Power Spectrum. . . 5

3. Block Diagram of Equipment Used in the
StUdy o o c o o o o o o o o o 25

A. Signal-to-noise Ratio versus Percent
Detection for 70 decibel SPL Noise
LQVBI O o 9 o o o o o o o o o 35

5. Signal-to-noise Ratio versus Percent

Detection for 80 decibel SPL Noise

mvel O O O O O 0 O O O O O Q 36
6. Signal-to-noise Ratio versus Percent

Detection for'90 decibel SPL Noise

Level . . . . . . . . . , . . 37

7. Experimentally Determined Thresholds. . . 38

iv

Appendix
A.
B.

LIST OF APPENDICES

Equipment Used in Study .

Response Form . . . .

Page
53
51+

CHAPTER I
INTRODUCTION

There is an increasing interest in and importance
being attached to the area of hearing research. One of
the specific problems that has attracted the attention of
researchers pertains to the distortion that occurs in the
impaired ear. What is the nature of this distortion, how
does it occur, and how might the effects of this distortion
be compensated for in hearing aid devices? If the answer
to the question pertaining to the nature of distortion
were known, the problems of the origination and the correc-

tion of the distortion might be more easily answered.

Background

There are many ways in which information regarding
the nature of this distortion might be uncovered. One
reasonable approach to this problem might be examined.
First, select a person who has one sick ear and one
healthy ear. Feed some sort of sound stimulus into the
sick ear, Feed the same stimulus into the healthy ear.
Make some provisions, however, to alter and distort this
stimulus entering the healthy ear. Instruct the subject
to change the nature of the stimulus entering the healthy

1

ear by means of these alterations and distortions so that

it resembles the sound entering the sick ear. If, then,
these distortions and alterations were to be analyzed,

some knowledge concerning the distortion that takes place

to the sound in the sick ear should be revealed. Two
questions would have to be answered before this hypothetical
study could be undertaken. What sort of sound stimulus
should be used, and what sort of alterations and distortions
should be introduced in this stimulus? Significant results
in the study could very well depend on the solution of

these problems.

The hearing mechanism, from the outer ear to the
lower centers of hearing in the menencephalon of the brain,
is basically composed of two types of energy systems. The
first of these is mechanical; the second, electro-chemical.
The mechanical part of the mechanism includes the parts of
the ear from the outer ear to the inner ear. In the inner
ear the stimulus is converted into nerve impulses (electro-
chemical energy) for transmission to the lower centers of
hearing in the brains. It would seem, therefore, that the
distortions characteristic of mechanical and electro-
chemical systems.

Distortions in the motion of mechanical systems are
introduced by, among other things, stiffness of the compon-
ents of the system, air resistance of the system, excessive

amplitude of vibrations, non-uniform density of the

components of the system, and the dissipation of energy
during vibration. By means of appropriate force-voltage
or force-current analogies, electrical circuits may be
devised which produce effects analogous to the vibration
of such mechanical systems. Thus such a circuit can be
used to study the distortional effects in the mechanical
system.

The distortions present in electro-chemical systems
are apparently less fully understood. It seems reasonable
to assume, however, that analog electrical circuits might
be devised to study the effects of this type of system also.
Thus one electrical circuit might be devised to study the
effects of distortion in both the mechanical and electro-

chemical parts of the hearing mechanism.

Statement of the Problem

What sort of sound stimulus should be used in such
a study? At the present time, most of the hearing testing
is being done with pure tone signals. Many of the dis-
tortions present in the electrical analog circuit would
be, however, characteristic of complex signals. It would
seem desirable, then, to use a complex signal as the basis
for such a study.l White noise is a complex signal which
is being used in testing if not quantitatively then quali-
tatively as masking. The desired alterations and distor-

tions could be introduced into a white noise stimulus.

There is, however, little information available concerning
the response of the normal human ear to distortion in
white noise. Some appropriate investigations along these
lines are needed, and this was the purpose of the present
study.

A band of white noise has a power spectrum which is
constant over all requencies within the bandwidth of the

noise. This is illustrated by means of Figure 1.

Figure 1
White Noise Power Spectrum

 

Power

 

 

Frequency

Suppose that at some frequency (or narrow band of fre-
quencies) a "spike" were introduced into the bank of noise.

This would appear as illustrated in Figure 2.

Figure 2

Distorted White Noise Power Spectrum

pl

[ p

Power - , e p

 

 

 

Frequency

The power increment between the tOp of this spike and the
level of the noise is, as noted on the graph, p. If,
then, the capability of the ear to detect such deviations
in the noise were to be investigated, some small bit of
knowledge concerning the response of the normal human ear
to distortion in white noise might be added. This was the
purpose of the present study.

Formally stated, the purpose of the present study
was to investigate the ability of the normal human ear to
detect signals in white noise. Further clarification of
the topic will follow.

There are several ways in which a spike might be intro-
duced into white noise. Perhaps one of the easiest would be
to superimpose a pure tone signal onto the noise. Denoting
the frequency of the signal by f, the spike on the white

noise would appear, upon superimposing the sine wave on the

noise, at a frequency f. Simply varying the frequency of
the sine wave would vary the location of the spike in the
white noise.

This procedure of impressing a signal on a band of
noise might sound familiar. It is, indeed, the basis for
many signal-to—noise studies which have been conducted.
Since this is the general procedure which was followed in
the present study, what can be said about the uniqueness of
the study? Review of many of the previous studies dis-
closes that the present investigation obtained data not
available in the other studies.

Most of these previous studies presented the sub-
jects with a band of white noise and then superimposed on
the noise the signal. The subject was then instructed to
adjust the level of the signal so that it was just distin-
guishable from the noise. A record of this point was
made. Such a precedure was repeated for various signal
frequencies and various levels of white noise. This data
yielded audiometric curves for the signals in the noise.
The present study presented to the subjects signals of
various frequencies and at various levels of intensity with
respect to the noise. The level presentations were made
independent of the control of the subjects. Moreover,
these levels were varied randomly when presented to the
subjects (several presentations at each level were made).

In accord with common practice, the signal intensity which

was detected by the subjects 50 percent of the time was
defined as the threshold. Lesser signal intensities were
detected by the subjects in fewer than 50 percent of the
presentations. Signal intensities greater than threshold
were detected by the subjects more than 50 percent of the
time. The data thus yielded information for an analysis of
percentage of detection. Such data, for several frequencies
and noise levels, were not found in any of the previous
studies. The information seems to be, however, an important
addition to the store of knowledge concerning the response

of the human ear.

Organization of the Thesis

Chapter Two of the thesis contains a short review of
the literature relevant to the present study. Chapter
Three contains a discussion of the procedures and equipment
employed in the study. Chapter Four presents the results
of the study and the statistical analysis of the data.
Chapter Five contains a short summary of the study, con-
clusions, and some possible implications for further re-

search.

CHAPTER II
REVIEW OF THE LITERATURE

Although no specific examples were cited, it was
mentioned previously that various studies concerned with
signal-noise ratio have been undertaken. This section
will attempt, among other things to illustrate generally
the type of work that has been done on the subject.

Background

Depending on the relative orientation of the re-
searcher, the investigation of signals in noise has been
approached from two viewpoints. The determination of
detectable signal-to-noise ratios and the determination
of masked audiograms are both concerned with essentially
the same thing. The earliest study discovered in the
literature approached the subject of signals in noise
from the latter viewpoint. Roger Galt, in 1929, determined
the noise audiograms for warble tones masked by various

environmental noises.l Among these noises were a brass

 

t~v-—v —- fi-v

1Roger H. Galt "Methods and Apparatus for Measuring
the Noise Audiogram,‘ The Journal of the Acoustical Society
of America, I, No. 1 (October, 1929),“IM7-57.

band, boat whistles, typewriters, and telegraph sounders.

The study was reported in the very first issue of The Journal
offithe Acoustical Society of America. It seems reasonable

to assume that earlier studies of signals in noise were con-
ducted. This study was one of the first published investi—
gations dealing with the topic.

One of the important studies concerned with noise
masking was reported by Fletcher and Munson in 1937.1 They
plotted masked audiograms for signals from 100 to 10,000
cycles per second. The masking was done with bands of random
noise. These bands were: 140 - 160 cps, 1050 - I250 cps. and
3000 - 3260 cps. 0n the basis of the final results of the
study they made some postulations concerning the mechanical
action of the ear in response to signals masked by noise.

The first use of the term "white noise" seems to have
been made about the end of 1945 by J. E. Hawkins, Jr., and
S. S. Stevens2 in a study conducted at the Psycho-Acoustic
Laboratories of Harvard University. This research was des-
cribed originally in a restricted OSRD Report #5387 under

the date of October 1, 1945. Until this time the masking

 

lHarvey Fletcher and w. A. Munson, "Relation Between
Masking and Loudness," The Journal ofthe Acoustical Society
of America, IX, No. 1 (July, 193777'1-10.

2J. E. Hawkins, Jr. and S. S. Stevens, "The Masking of
Pure Tones and of Speech by White Noise," The Journal of
(acoustical Society of America, XXII, No. l (JuIy, 1950),
-13.

lO

noise used in the studies was described as random, thermionic
noise. Whether some of the studies did, in fact, use white
noise before this time may be Open to question, but the term
was not used before this time. This particular study was
concerned with the effects of masking on pure-tone presenta-
tions and the resultant threshold shifts. The data were
obtained by presenting the signals monaurally to the subjects
and allowing them to vary the levels of the signals until they
were just distinguishable from the masking noise. Curves
were plotted for signals of various frequencies masked by
noise of various intensities. The researchers then plotted

a series of masked threshold curves. They found that the
masking produced by white noise is directly proportional to
the level of the noise. That is, when the level of the

noise is raised by 10 dB, the masked threshold is also
increased by 10 dB.

A related study by George Miller was published in
ThefiJournal of Acoustical Society of America.1 This was one
of the first published studies to make use of the term white
noise (reference is made, however, to the earlier work by
Hawkins and Stevens in this study). Adding further to the

knowledge concerning noise and masking, this study

 

1George A. Miller, "Sensitivity to Changes in the
Intensity of White Noise and Its Relation to Masking and
Loudness," The Journal of the Acoustical Society of America,
XIX, No. 4 (July, 191177, 609—19. *

 

11

investigated just detectable increments in the intensity
of noise, and of signals masked by noise.

A study similiar in some respects to the present one
was published by Schafer and Gales in 1949.1 They plotted
the transition curves (recognition probability as a function
of level) for an 800 cycle tone. Punched tape switching
apparatus was utilized to randomly vary the levels of the
signal. The transition curves were also determined and
plotted for combinations of four to eight tones masked by
the noise.

In 1961 Small and Minifie conducted an investigation
similiar in many respects to that of Hawkins and Stevens

described earlier.2

Using frequencies of 250, 500, 1000,
2000, 4000, and 8000 cycles per second, they determined

the shift of threshold from masked to unmasked presentation.
Noise levels of 60, 90, and 110 dB were used for the
masking. Confirming the results of the earlier work of

Stevens and Hawkins, Small and Minifie found that there is

"nearly a one to one relationship between the masker level

 

*7

lTillman H. Schafer and Robert S. Gales, "Auditory
Masking of Multiple Tones by Random Noise,” The Journal of
thegAcoustical Society of America, XXI, No. A (July, 19H9):

392498.

2Arnold M. Small, Jr. and Fred D. Minifie, "Intensive
Differential Sensitivity at Masked Thresholds," Journal
of Speech and HearingfiResearch, IV, 164-71.

 

12

and amount of masking. For example, if the masker level
is increased by 20 dB, so also is the amount af [sic.]
masking."l

This review of the literature has considered several
important investigations concerned with signals in noise.
The list of these studies could be expanded. It seems to
this writer that further review would provide needless
repetition.

Studies Related to Present
Experimental Design

 

Prior to the actual gathering of data the experimental
design of the study must be determined. Usually the re-
searcher is quite certain as to the variables which are to
be investigated. This doesn't lessen the effect of other
variables on the results, however. The researcher may then
decide to ignore these other variables. Or he may design
the study so that the effects of these variables is constant
and, hopefully, cancel out in the final analysis of the data.

There are many factors which affect the threshold
determinations of signals in noise. Signal-to—noise ratio,
frequency of the signal, duration of signal presentation,
transients in switching, mode of presentation (binaural

versus monaural) and foreknowledge of the stimulus all affect

 

llbld.,-p. 168.

13

the final results. This study was primarily concerned
with the signal-to-noise ratio and signal frequency
variables. Since the purpose of the study was to obtain
the minimum thresholds for signals in noise, factors not
of direct interest in the study had to be treated in the
design such that their overall effect on the study would
be to give these minimum thresholds. It was therefore
necessary to refer constantly to the literature for the
purpose of determining the manner in which these factors
should be treated in the investigation. As a part of the
review of the literature, then, this aspect of the study
will be considered.

One of the variables mentioned as the duration of the
presentation as a factor affecting the threshold determina-
tion. Goldstein and Kramer found that "where reactions for
longer tones were explored, greater sensitivity was shown
for the longer tones than for 150-200 millisecond tones."l
There seemed to be, in the words of the authors, a "linear
trading relation between time and intensity."2 As the

tones were increased in duration, the sensitivity of the

subjects tended to increase. This was true in the region

m we a W. W

1Robert Goldstein and Joan C. Kramer, "Factors Affect-
inc Threshold for Short Tones,” Journal of Speech and Hearing
Research, III, No. 3 (September 1960), 249-56.

'QIbid., p. 255.

14

of tonal intensity from 20 to 200 milliseconds. As the
tones increased in length from 200 milliseconds, the
thresholds continued to get lower but at a slower rate.
This would indicate an asymptotic behavior of this linear
trading function for presentations of greater duration.
Since no graphs were included in the results of the study,
the exact nature of this asymptotic relation is not known. are
It might be assumed, however, that no further significant E
changes in sensitivity would be apparent for tones of 3

duration greater then, say, one second. Regarding the

 

duration of the masking stimulus, Egan has shown that the

{I a

masked threshold is essentially independent of the duration
of the masking stimulus.1 The results of these two studies
would indicate, therefore, that minimum threshold would be
obtained for signals of at least one second duration. The
masking could be constant with respect to time.

Transients in switching and the rapidity of the
switching action were also factors mentioned as having an
effect on the final threshold results.* Montgomery has shown

that for optimum threshold determination conditions, the

 

1James P. Egan, "Independence of the Masking Audio ram
from the Perstimulatory Fatigue of an Auditory Stimulus,‘
The Journal of the AcousticalfiSociety of America, XXVI, No. 4

(leY: 1955): 737-40.

15

transition between tones should be abrupt, instantaneous,

and silent.1 A gradual transition between tones, such as
that of a sinuosidal intensity variation, is less easy to
detect than an abrupt transition. Wright, also investigating
switching transients, presented the subjects with 500-
millisecond tones beginning at the time axis and rising to
maximum amplitude in l/4 cycle, 1 1/4 cycle, 2 1/4 cycle,

5 1/4 cycle, and 100 milliseconds.2 These presentations made

use of 500, 1000, 2000, 3000, 4000, and 6000 cycle tones.

. '.-:4rn§s..-iv‘. h~ \fi Tee-£- “a

He found that although switching transients present in pure-

 

tone signals with rapid rise-decay times are quite apparent

V‘

at supra—threshold levels, the degree to which they affect
the measurement of threshold can be relatively slight.
These results indicate that switching transients have no
appreciable effect upon the threshold determinations for
the normal ear. In terms of the objectives of the present
study, then, the switching should be abrupt and instantaneous.
The switching transients should have no effect on the final
results.

Regarding monaural versus binaural presentation of

the stimulus, Chappel, Kavanaugh and Zerlin found that the

W

1H. C. Montgomery, "Influence of Experimental Technique
on the Measurement of Differential Intensity Sensititity of
of the Ear,” The Journal of the Acoustical Society of America,
VII, No. 1 (July, 1935), 39-43.

2Herbert N. Wright, "Switching Transients and Threshold
Determinations," Journal of Speech and Hearing Research,I,
No. 1 (March, 1958), 52—60. *

16

average intelligibility score for binaural presentation of
the stimulus was about 60 per cent, approximately 20 per cent
higher than the average score for the monaural presentation.l
Although this study concerned intelligibility scores and not
thresholds for pure tones, it seems reasonable to assume
that the pure-tone threshold would also be lowered by binaural
presentation of the stimulus. Thus, in terms of the minimum
threshold, binaural presentation of the signal should be
make.

Harris found that foreknowledge of stimulus character—

istics also affect the final threshold determinations.2

This
factor may operate to shift the threshold determinations,
under certain conditions, by 10 dB or more. As he notes in
the concluding remarks of the study:

One may suspect that what one is measuring over a

certain signal-to-noise test session may be not the

subject's inherent auditory sensitivity at all but

the slope of his learning curve; and there may be

little relation between the slope of learning ver-

sus the asymptotic sensitivity index.

Again, in terms of the minimum threshold, foreknowledge

of the stimulus characteristics should be provided

 

*

lRichard G. Chappell, James F. Kavanagh, and Stanley
Zerlin, "Monaural versus Binaural Discrimination for Normal
Listeners," Journal of Speech and Hearing Research, VI, No. 6
(September, 1963), 263- 269.

2J. Donald Harris, "A Factor Analytic Study of Three
Signal Detection Abilities," Journal of Speech and Hearing
Research, VII, No. 1 (March, 1964), 7l—78.

 

3Ibid.

17

to the subjects. For this reason, a sample presentation of
the signal was provided for each subject prior to the actual
gathering of the data.

In summary, previous studies have indicated that, for
minimum threshold determinations, the following considera-
tions should be incorporated into the final design of the
study: the signal should be of at least one second duration,
switching should be abrupt and instantaneous, the signal
should be presented binaurally, and the subjects should have
foreknowledge of the characteristics of the signals. The
effects of masker duration and of switching transients should
have no significant effects on the final results of the
study. The experimental design was conceived with these

considerations in mind.

Classical Psychophysical Methods

The field of psychophysics has grown in importance
immensely in the last few years. Psychophysics is
basically concerned with the study of the psychological
effects of physical stimuli on the human body. One of
the more important concepts in the field is that of a
threshold. Threshold can be defined as "a boundary separa-
ting the stimuli that elicit one response from the stimuli
that elicit a different response."1 Two types of thresholds

 

1Robert S. Woodworth and Harold Scholsberg, Experi-
mental Psychology (New York: Henry Holt and Company, 1958),

Do 193.

18

may be distinguished. One is often referred to as the
stimulus threshold. This threshold separates the stimuli
which elicit a response from those which elicit no response.
The second type of threshold is known as the difference
threshold. Tho stimuli which the observer can just distin—
guish as being different determine this threshold. Due to
the importance of thresholds in the study of human responses
to various stimuli there have been developed several
psychophysical methods for the determination of these thresh-
olds. The classical psychophysical methods are known as

The Method of Average Error, The Method of Limits, and The
Frequency Method. Each method has its own advantages and
disadvantages and its own field of application.

The Method of Limits is the only direct method of
locating a threshold. Two categories which elicit different
responses from the observer are used in this method. In
the case of the stimulus threshold, one of the categories
might be the region in which the observer does not detect
the stimulus. The other category would then include the
region in which the observer does detect the stimulus. The
stimulus is then varied between these two categories and the
response of the observer recorded. The threshold is taken to
be the value of stimulus which locates the observer's
response shift from one category to the other. If a large
number of such trials are made and the results averaged, this

procedure locates quite accurately the threshold point.

 

 

19

The second psychophysical method mentioned was
The Method of Average Error. This is normally conducted
by instructing the observer to adjust a variable stimulus
until it appears equal to a given standard. If this
procedure is repeated a number of times, the results can
be analyzed mathematically to determine the desired
thresholds. The method may be altered somewhat to allow
the experimenter to have control over the variable stimulus
intensity. The observer then judges at what point the
variable stimulus intensity appears equal to the intensity of
the standard stimulus.

The third classical psychophysical method and the one
employed in the present study is The Frequency Method. In
this procedure the variable stimulus is compared with the
standard stimulus many times and the relative frequency of
the different response categories is counted. This may be
done with many intensity levels of the variable stimulus.
These data may then be analyzed statistically and the thresh-
old located at the 50 per cent response point between one
category and the other. This method is particularly useful
in studying the transition zone between stimuli which can
nearly always be detected and stimuli which are rarely
detected. The threshold may then be taken as the stimulus
intensity which elicits a response 50 per cent of the time.

If this transition zone for any sensory modality of

the human body is plotted in the form of per cent detection

20

versus intensity of stimulus the resultant curve is an ogive.
This is due to the fact that any sensory function variation
tends to show as approximately normal distribution of values.
The ogive is simply the cumulative form of this normal dis-
tribution curve.

Certain modifications of The Frequency Method have been
made by various experimenters. Perhaps the best known of
these modifications was devised by Muller and Urban and is
known as the Muller-Urban weights. Muller and Urban found
that sampling errors may occur in the course of obtaining
data and that these errors, due to the manner in which the
data are analyzed, affect the extreme points of the transi-
tion zone more than the central points. For this reason
they developed a weighting procedure by which the central
points are given more weight than the end points in the
analysis of data.

Such researchers as Peterson and Birdsall,l Tanner

and Swets,2 and Tanner, Swets and Green3 have recently

 

1w. w. Peterson and T. G. Birdsall, The Theory of
Signal Detectibility, Electronic Defense Group Technical
Report No. 13 (Ann Arbor, Mich.: The University of Michigan,

1953-)

2Wilson P. Tanner and J. A. Swets, "A Decision-Making
Eheoiy of Visual Detection,” Psychological Review, LXI (1954),
01- O9.

 

3Wilson P. Tanner, J. A. Swets, and D. M. Green, Some
General Properties of the Hearing Mechanism, Electronic De-
fense Group Technical Report No. 30 (Ann Arbor, Mich.: The
University of Michigan, 1956)

W‘s-and. fim‘afl

r’ a i

5)

I

21

expressed dissatisfaction with the classical psychophysical
methods. These classical methods still form the basis for

most present studies of sensory perception, however.

 

CHAPTER III

PROCEDURES AND EQUIPMENT

Subjects
Two subjects, both male graduate students in Speech

and Hearing Science, were used for the purposes of the
study. Both subjects had normal hearing. For the pur-
poses of this study, a subject was considered to have
normal hearing if his threshold for 500, 1000, or 2000
cycle per second pure tones was no greater than 10 decibels

re USPHS in either ear.

Procedures

 

A constant level of white noise was presented
continuously and binaurally through headphones to the
subjects. Noise levels of 70, 80, and 90 dB SPL were
used. At each of these levels, 160 two-second presenta-
tions of a 500 cycle tone, a 1000 cycle tone, and a 2000
cycle tone were superimposed on the noiSe. Each such set
of 160 presentations of the pure tone consisted of ten
presentations at each of 16 intensity levels. Since these
intensity levels varied in one-dB.steps, a total pure-tone
intensity range of 16 dB was encompassed for each set of

presentations. The intensity variations were made randomly.

22

23

The exact placement of the 16 dB pure-tone intensity
range described above was determined immediately before
each set of presentations. The highest level of the range
was chosen to be a point at which both subjects could
clearly hear the tone in the noise. The lowest level was
chosen to be a point at which neither subject could detect
the signal in the noise. This range varied somewhat for
each set of presentations and the exact figures for the

ranges used are given in Table 1.

Table 1

PURE-TONE SIGNAL INTENSITY RANGES

 

 

Signal Signal Intensity
Noise Level Frequency Range
70 decibel SPL 500 cps -22 0 to -37.0 dB SPL
" 1000 cps -15.5 to -30.5 dB SPL
” 2000 cps —l3.0 to -28.0 dB SPL
80 decibel SPL 500 cps -l2.5 to -27.5 dB SPL
” 1000 cps -12.0 to -27.0 dB SPL
” 2000 cps —18.5 to -33.5 dB SPL
90 decibel SPL 500 cps —ll.6 to -26.6 dB SPL
" 1000 cps -10.6 to —25.6 dB SPL
" 2000 cps -lA.0 to -29.0 dB SPL

 

A small red signal light indicated the pure-tone
presentations. This visual indication was necessary since
the lower pure-tone intensity levels were not always

detectable by the subjects and the presence of a stimulus

interval had to be known if the subjects were to maintain
an item count.

The responses of the subjects were recorded on
Special response sheets. A set of two response sheets was
used for each set of 160 presentations (see Appendix B).
Each set of two sheets contained 160 pairs of the letters
"s" and ”n". The letter "s” was used to indicate signal,
the letter "n” to indicate noise (no signal).

The subjects were instructed to listen to the noise
in the headphones and, simultaneously, to watch the signal
light. If, when the light flashed, they were able to
detect a signal in the noise they would circle the letter
"s" on the response sheet. If the light flashed and they
were unable to detect a signal, they would circle the
letter ”n"

The experimental data were obtained in a converted
classroom measuring approximately 20 by 30 feet. The
room has plastered walls, a hard floor, and is surrounded
on two sides by a blackboard. For this reason the data were
obtained on a week-end when the background noises which
might have possibly interferred with the study were at a
minimum. The controlled white noise level in the experiment
exceeded that in the test room while the experiment was
being conducted. In order to minimize visual distractions

the subjects were seated on chairs facing away from the

equipment used in the study. The small signal light was

 

25

placed in front of the subjects such that it could be

clearly seen by them.

Equipment

 

The block diagram of the equipment used in the study

appears in Figure 3.

Figure 3

Block Diagram of Equipment Used
in this Study

 

 

 

 

 

 

 

 

 

 

 

 
  
  
   

 

 

 

 

 

 

 

 

  

 

m I
Random
Sine Wave Line
Generator “"" Switching Am--
and -'——‘ ——-' lifier
Attenuator P
Mixer Headphones
Line
White Noise Am-

Generator plifier

 

 

 

 

For a detailed list of the exact equipment used, See
Appendix A.

The white noise was fed into one chanell of the
electronic mixer unit. The pure-tone signal was fed into
the second channel of the unit. This sine wave, as described
previously, was varied in intensity through the use of the

random switching unit and the 16 channel attenuator unit.

26

The random switching unit consisted of an assembly
containing twenty sets of contacts (or channels), sixteen
of which were utilized in this study. The lower part of
each set of contacts consisted of an assembly of twenty
copper rings mounted on nylon bushing so as to insulate
them from each other and from the rest of the switching
mechanism. Resting on each of these copper rings was
a short brass strip. Each combination of copper ring and
brass strip provided a normally-closed switch. The
switch might be opened simply by lifting the brass strip
from the copper ring. This opening and closing of the
contacts was achieved automatically by feeding a programmed
card through the unit between the copper rings and the brass
strips. The card normally prevented the strips from
touching the rings thus holding the switches open. A hole
punched in the appropriate position of the card would.
allow one of the strips to contact the ring below it,
thus closing that particular channel. To achieve random
switching these holes in the card were punched in a random
manner. That is, each of the sixteen channels to be used
was assigned a number from one to sixteen. These numbers
were then selected from a table of random numbers and the
holes were punched in the cards corresponding to the order
in which the numbers had been selected. Since ten presenta—
tion at each level were desired, each of these numbers was

selected ten times in the course of compiling the list of

random numbers.

 

27

The cards used for the switching were six inches
wide and about two feet long. A small one—rpm motor
driving two small rubber rollers fed the card through the
unit. The diameter of each of these rollers was one and
one-quarter inches.

In the course of designing the unit it was found that
square holes rather than round holes in the card resulted
in more consistent operation of the mechanism. Thus it
was necessary to have a square hole punch designed and
built for the purpose of the study.

The duration of the signal presentations was con-
trolled by two factors: The size of the holes in the
card and the rate at which the card was fed through the
unit. Although it was possible to vary somewhat the size
of the holes, adjusting the rate of card feed through the
unit was preferable in controlling the signal duration.

A presentation time of about two seconds was achieved
through the use of a 5 to 3 pulley drive reduction on
the one-rpm motor.

The attenuator unit consisted of sixteen channels,
each of which contained an adjustable potentiometer. Each
of these channels was connected to one of the sets of
contacts of the switching unit. Each potentiometer was
calibrated individually to give the desired amount of
attenuation for that particular channel. These procedures

for calibration were quite simple. A pure-tone signal of

 

 

28

known intensity (as measured by a sound pressure level
meter) was fed into the potentiometers. The potentiometers,
were then adjusted so that the output of each potentiometer,
again as measured by the sound pressure level meter, was

the desired amount below the input. Although different
pure-tone intensities and frequencies were used in the
study, no change in the initial calibration of the

potentiometers was necessary.

L!

 

CHAPTER IV

RESULTS AND ANALYSIS OF DATA

Data Reduction

 

It was mentioned in Chapter II that for each sensory
modality of the human body a transition region can be
found. This is the region that ranges from the point at
which the stimulus is rarely detected to the point at which
the stimulus is nearly always detected. If one obtains the
data for such a region and plots it graphically the
resultant curve turns out to be an ogive.

If an experimenter is interested in plotting this
ogive curve he may obtain his data by some appropriate
method and then proceed to plot the curve from these data.
Because of random error, the ogive will, of course, not
be perfect. Some trial and error curve fitting must be
done. This can be done visually but the results of such
procedures usually leave much to be desired in the way of
accuracy. This is particularly true in the case of com-
plex curves such as the ogive curve. Thus some other
method of curve fitting should be employed.

There exist, for straight lines, quite accurate
mathematical methods of curve fitting. One of these is

the method of least squares. This method yields the line
29

30

through the points such that the squares of the y-axis
deviations of the points from this line are a minimum.

The experimenter who has obtained some sort of complex
data would thus do well to determine whether the data can
be transformed to some coordinate system which would yield
a straight line. Linear curve fitting techniques could
then be employed.

In the case of the data for the transition region,
such a transformation can be made. The original data are
in the form of per cent detection plotted against stimulus-
intensity. If the per cent-detection data of the ordinate
is transformed to normalized standard-score units (z-scores),
the resultant graph is linear if the transition function is
a normal ogive. The curve fitting can then be done on the
reduction of the linear data. The results can then be
transformed back into the original per cent-detection versus
stimulus-intensity form and the desired ogive plotted.

This short background discussion was presented since
it describes the manner in which the data of the present
study were analyzed. The raw per cent—detection versus
signal-to—noise ratio data were tabulated. Such a set of
data was obtained for each subject for each of the nine
conditions of frequency and noise level. Since there were
two subjects, two sets of data for each set of conditions

were actually obtained. The final set of data for each

31

set of parameter conditions was obtained by simply averaging
the data of the two subjects.

The per cent-detection data of the ordinate were
transformed into z—scores and the resultant signal—to-
noise ratio versus z-score units were plotted. Then, by
the method of least squares, a straight line was fitted
to each set of data. The results were then retransformed
back into the original form of per cent-detection versus
signal—to-noise ratio and the desired ogive curves were
plotted.

The method of least squares yields the slope, m, and
the y-intercept, b, of the line of best fit. This line can,
of course, be plotted and points read from the line. For
the purposes of this study a more accurate approach was
used. The lines were not actually plotted but the location
of points on the lines was determined mathematically. Such
information is easily obtained since the slope and y-inter—
cept of the line of best fit are known.

Some problems were encountered in the analysis of the
data. One such problem was concerned with the transforma-
tion of per cent-detection points into z-scores. This is
easily done except when 100 per cent and 0 per cent detec-
tion points must be transformed. Theoretically, 100 per
cent-detection corresponds to a z—score of +00 , and 0
cent detection to a z-score of -CK>. Obviously such points

cannot be used in the mathematical analysis of the data.

32

A z-score value was arbitrarily assigned to these values.
Whenever a 100 per cent detection was encountered in the
data, a z-score of 2.50 was assigned to the value. When-
ever a 0 per cent-detection point was encountered a z-score
value of -2.50 was assigned. The z-score value of 2.50
actually corresponds to a 99.5 per cent detection value.

This procedure would correspond very roughly to that

T- T"? TF3? 'a'u

advocated by MUller and Urban. They suggested assigning
weights to all the z-score values, the weights being the
greatest near the center of the curve and the least at

the extreme ends. The procedure of assigning a z-score

value of 2.50 in place of a value of +c¢lhas the effect of
greatly de-weighting the extreme points for the purpose of
the analysis.

Another problem was encountered in some of the data.
To illustrate this problem, refer to the hypothetical set

of data presented in Table 2.

TABLE 2
PER CENT DETECTION DATA

 

V— V V V .____

Signal—to-Noise

 

Per Cent Detection Ratio
100 . . . . . . . . . . -15 decibel SPL
100 . . . . . . . . . . -16 decibel SPL
80 . . . . . . . . . . -l7 decibel SPL
100 . . . . . . . . . . -18 decibel SPL
100 . . . . . . . . . . -19 decibel SPL
90 . . . . . . . . . . -20 decibel SPL

80 . . . . . . . . . . ~21 decibel SPL

 

33

Obviously the data are quite consistent with the exception
of the point for ~17 dB SPL. Was this point detected only
80 per cent of the time due to the masking effect of the
noise or did some other factor account for this failure of
the subjects to detect the tone in some of the presenta-
tions? For example, did an equipment malfunction account
for the low detection precentage at this point (that is,

was the signal actually presented less than ten times)? The
answers to these questions could significantly affect the
final results of the graph. There were two points of
intensity less than -17 dB which were detected 100 per cent
of the time. Intuitively, one feels that the probability
of detecting these points 100 per cent of the time by chance
is much lower than the probability of an equipment failure
accounting for the drop in detection at -17 dB. In other
words, the probability of detectingby chance all presen-
tations at -18 dB is quite small due to their being scattered
randomly among 160 presentations. 0n the other hand, there
is a much greater probability, due to the nature of the
equipment involved, that a malfunction of equipment
accounted for the low detection precentage at -17 dB. Thus
one seems justified, on the basis of probability alone, to
assign a 100 per cent detection value to the -17 dB point.
Closer examination of the data appeared further to justify
this procedure. In all cases in which a signal-to-noise

ratio was detected less than 100 per cent of the time, and

34

in which a signal of lesser intensity was detected 100
per cent of the time, it was found that the very same
presentations were missed by both subjects. This would
seem to indicate also equipment malfunction accounting

for this effect.

assess.
The graphical results of the investigation are
presented on the following Iknur pages in Figures 4, 5, 6
and 7.
This is the final data, having been compiled and

analyzed as previously described.

Discussion

At 70 dB, the threshold for the 1000 and 2000
cycle tones is somewhat higher than the threshold for the
500 cycle tone. That is, 70 dB of noise more effectively
masks 1000 and 2000 cycle tones than it does 500 cycle
tones. Keeping the nature of white noise in mind, one
might suspect that this would indeed be the case.

White noise has a power spectrum which is constant
over all frequencies within its bandwidth. The energy
of the noise, however, is concentrated at the higher
frequencies. Thus more noise intensity is required to
mask tones of lower frequencies. This effect is illustrated
quite well by the first set of data. If the 50 per cent

detection point is taken as the threshold, the threshold

Percent—Detection

35

Figure 4

Si'gnal-to—noise: Ratio versus Percent-Detection
for 70 dB SPL Noise Level

100

80

60

40

2O

 

0’
D

 

 

A~----- 500 cps tone

1000 cps tone
- 2000 cps tone

 

 

'V

l
-18

I r l
'30 *26 '22

Signal-to-noise ratio (dB SPL)

-lLl

36

Figure 5

Signal-to-noise Ratio versus Percent-Detection
for 80 dB SPL Noise Level.

 

 

 

 

 

A—-- - 500 cps tone
0 1000 cps tone
0 _ 2000 cps tone
.. D D '0
100 c: 0.2/5 090
80 ‘
.3.
l, 60 ‘
O
3
A
4;; no -
0)
0
g.
Q)
04
20 4
O » r ~ * T ' Th , T +3 r A j
'36 '32 -23 *2“ -20 -16 ~12

Signal-to-noise Ratio (dB SPL)

Percent-Detection

37

Figure 6

Signal-to-noise Ratio versus Percent-Detection
for 90 dB SPL Noise Level

A—-—-—-—- 500 cps tone
O-————-— 1000 cps tone
0.....--—— 2000 cps tone
100‘ AM
80"
60'-
40"
20"
O in

 

 

 

Threshold Signal-to-Noise Ratio (dB SPL)

32

30

28

26

24

22

2O

1

 

38

Figure 7

Experimentally Determined Thresholds

500 cps tone -—-——-——A

Q 1000 cps tone __._._——..0
\ 2000 cps tone ..._......-.—n

 

 

T "I '
70 80 90
Noise Level (dB SPL)

39

for the 1000 and 2000 cycle tones is about 8 - 9 dB

higher than the threshold for the 500 cycle tone. Although
the threshold for the 1000 cycle tone was about 1 dB lower
than the threshold for the 2000 cycle tone, there was, as
will be shown later, no significance in the difference.

The difference is probably due to random error.

For a noise level of 80 dB the threshold for 2000
cycle tones is again lower than the thresholds for either
the 1000 cycle or 500 cycle tones. Again, these differ-
ences were not shown to be significant and were probably
due to random error in the course of gathering the data.
Non~linear response of the headphones, variation in the
responses of the subjects, error in the measuring equip—
ment, and so forth could account for the differences.

At a noise level of 90 dB SPL the threshold for the
500 cycle tone is somewhat lower than that for the 1000
cycle tone. The threshold for the 2000 cycle tone is
about the same as the threshold for the 500 cycle tone.
Again, these differences were not significant and were

probably due to random error.

Statistical Analysis
Since some differences did exist in the experi-
mentally determined thresholds under different conditions,
it was felt that further analysis of the data was in

order. Such analysis could reveal whether the differences

r ”“1;

 

40

were statistically significant or whether they were the
result of random error. An analysis of variance there-
fore was performed on the data in an attempt to answer
these questions.

A two-way analysis of variance model was used as
the basis for the analysis.1 The analysis revealed that,
at the .05 significance level, differences existed be-
tween the different noise levels and between the different
frequencies. In addition, a significant interaction was
revealed. Since the interaction could very well be
responsible for the significance between the frequencies,
and between the noise levels, further examination of the
data was carried out. The summary table for this analysis
is presented as Table 3.

Examination of Figure 7 suggests that the interaction
of the 500 cycle tone with the 70 dB SPL noise level
could be responsible for the significant results presented
in Table 3. 0n the basis of this assumption, an additional
of variance was performed on the data after the 500 cycle-
70 dB SPL noise level call had been dropped from the table.
The results of this analysis are presented in Table 4.

Since no significant differences are illustrated

in this table, it is apparent that the 500 cycle tone at

 

 

Y- —v~

1Hubert M. Blalock, Social Statistics (New York: Mc-
Grew-Hill Book Company, Inc., 1960), p. 255.

 

41

TABLE 3

ANAYLSIS OF VARIANCE SUMMARY TABLE

 

 

m i 2
Source of, Sum of Degree of Estimate of
Variation Squares Freedom Variance F
Total 181.01 17
Between
Subclass 155.16 8
Noise 28.07 8 14.03 4.88*
Frequency 47.87 2 23.94 8.34*
Interaction 79.22 4 19.80 6.90*
Error 25.85 9 2.87

 

* Significant at .05 level of confidence

 

TABLE 4
ANNALYSIS OF VARIANCE SUMMARY TABLE

 

 

 

“.9: am
Source Sum of Degrees of Estimate of
Variation Squares Freedom Variance F
Total 60.50 15
Between
Subclass 38.55 7
Noise 4.65 2 2.32 .85
Frequency 13.47 2 6.74 2.46
Interaction 20.43 3 6.81 2.49
Error 21.95 8 2.74

42

70 dB masking level did, in fact, account for the signi-
ficance shown in thefirst analysis of variance.

The results of the procedures outlined above allow
one to assert that the differences in the experimentally
determined thresholds, except for the 500 cycle tone at
70 dB SPL noise level, were due to random error in the
course of gathering the data. The 500 cycle threshold
at 70 dB SPL noise level was statistically significant
from the other subclasses at the .05 level. Some possible
reasons for this difference were mentioned earlier in the

chapter.

 

CHAPTER V

SUMMARY AND IMPLICATIONS FOR
FURTHER RESEARCH

Summary and Conclusions

 

Transition curves for 500 cycle, 1000 cycle, and
2000 cycle tones masked by 70 dB SPL, 80 dB SPL, and
90 dB SPL intensity levels of noise were experimentally
determined. From these curves the threshold points
at which the subjects detected 50 per cent of the presen-
tations were determined. The threshold for the 500 cycle
tone masked by 70 dB SPL of noise was significantly
lower than the thresholds for the other sets of conditions.

Previous studies have indicated that the amount of
masking is directly proportional to the level of the
masker; that is, when the intensity of the masker is
increased by 10 dB, so also is the masked threshold.
The results of the present study confirm these findings.
The average threshold for the subjects at the three noise
levels was about 22 - 23 dB below the level of the noise.
This means that the threshold for the tones increased in
direct proportion to increases in the level of the noise.
The overall effect was to keep the threshold for signal-

to-noise ratios at constant value.

43

 

44

Further conclusions regarding the response of the
hearing mechanism to the type of sound stimulus used in
this study cannot be made at this time. More information
will be needed for such conclusions to be drawn.

The response of the subject as to whether he hears a
certain presentation or does not hear a presentation is
determined on the basis of pass-fail criteria. That is, f“"
the subject sets standards for identification of the .'
signal. If the signal meets or surpasses these standards

the subject reports that he heard the signal. If the

 

signal does not meet these standards the subject reports fig,
that he has not heard the signal. This pass-fail criterion
is not defined in terms of absolute physical measurements
but rather in terms of the response of the auditory system.
It has been hypothesized that the response of the auditory
system is not constant but varies from moment to moment.
This accounts for the fact that signals of certain inten-
sities may be detected only part of the time. It is
basically this pass-fail criterion which determines the
threshold obtained for the subjects. The actual location
of this point and thus the threshold obtained may vary
under different conditions. For instance, the instructions
which are given to the subjects may affect this point.

In the case of the present study, the subjects were
familiar with the study and therefore were aware of the

procedures to be used. They were aware, for example,

45

that the signal was being presented each time that the
signal light flashed, even though some of these presen-
tations were not audible. It might be advisable, in
further studies of this sort, to advise the subjects that
a signal would not necessarily be presented each time
that the signal light flashed. This would provide some
actual uncertainty as to whether the signal did exist
or did not exist for some of the presentations.

One might suspect that the subject's knowledge of
a signal presentation each time that the light flashed
might lower the pass-fail criterion. That is, he might
identify signal presentations which wouldn't have been
identified had he not known that a signal accompanied
each flash of the signal light. In the present study it
is highly probable that the opposite effect was true.
The subjects were aware that they were supposed to detect
some of the signals and not detect some of the signals.
Thus it seems reasonable to assume that the criterion was
not lowered but actually raised. This would assure that
some of the signal presentations would be undetected. A
repeat of this study using different instructions for
the subjects might well result in lowered, or at least

different thresholds.

 

{rt

46

Implications for Further Research

 

Several recommendations for further study along the
present lines could be made. The scope of the present
investigation could be widened to include a greater
number of noise levels and signal frequencies. It
might be desirable to use noise levels from 20 dB SPL
upwards to those of the present study. Also, additional g
frequencies could be added. Alth0ugh they are out of the a
speech range, frequencies to 15,000 or 20,000 cycles per

second might be investigated.

 

It might be interesting to note whether other
types of masking by noise would give results comparable
to those of the present study. Specific narrow bands of
white noise might be used as the masking stimulus. Re-
search has indicated that the band of white noise extending
from one octave below to one octave above the frequency of
the signal being masked is responsible for the majority
of the masking. Plotting the transition curves using these
limited bands of white noise might result in some
interesting data.

The curves for transition regions might be plotted
using different types of signal stimulus. The stimulus
might be some sort of tone, or it might be speech sounds.
The transition curves for different speech sounds might

be plotted and the results compared. Two main pieces of

47

information could be obtained from this sort of investi-
gation. First, the threshold in terms of signal-to-noise
ratio could be determined. Second, from the slope of the
transition curves, information regarding the ability of
the ear to detect small intensity changes in the different
Speech sounds could be obtained.

This study was planned, as previously explained,
to be the first step in a series of investigations leading
ultimately to more complete knowledge about the types of
distortions occuring in the hearing mechanism. Such

studies could provide much valuable information concerning

steps that might be taken in compensating for these hearing

losses. The present study was initiated in terms of an
investigation concerned with the ability of the ear to
detect amplitude distortions in white noise. Signal-to-
noise ratio may, however, be interpreted in this way.
Certainly the signal is presenting amplitude distortion in
the noise. The next step in this series of studies might
be to measure the effects of other types of distortions on
the ear. Harmonic distortion, intermodulation distortion,
and phase distortion are only a few examples. White noise
could be used as the stimulus. Such studies might contri-
bute a wealth of information concerning the operation of

the normal and impaired ear.

 

BI BLI OGRAPHY

48

 

BIBLIOGRAPHY

Books

Baird, D. C. Experimentation: An Introduction to Measure-
ment Theory and Experimental Desigp. Englewood
Cliffs, New Jersey: Prentice-Hall, Inc., 1962.

 

Blalock, Hubert M., Jr. Social Statistics. New York:
McGraw-Hill Book Company, Inc., 1960.

 

Guilford, J. P. Psychometric Methods. New York: McGraw-
Hill Book Company, Inc., 1954.

Hirsh, Ira J. The Measurement of Hearing. New York;
McGraw—Hill Book Company, Inc., 1952.

 

Woodworth, Robert S. and Schlosberg, Harold. Experimental
Psychology. New York: Henry Holt and Company,
1958.

 

 

Periodicals

Chappell, Richard G., Kavanagh, James F., and Zerlin,
Stanley. ”Monaural versus Binaural Discrimination
for Normal Listeners," Journal of Speech and
Hearing Research,VI, No. 6 (September, 1961),
263-269.

 

 

Egan, James P. "Independence of the Masking Audiogram from
the Perstimulatory Fatigue of an Auditory Stimulus,"
The Journal of the Acoustical Society of America,
XXVI, No. 4 (July, 1955), 737-40.

Fletcher, Harvey and Munson, W. A. "Relation Between Masking
and Loudness,” The Journal of the Acoustical Society
of America, IX, No. 1 (July, 1937), 1-10.

 

Galt, Roger H. "Methods and Apparatus for Measuring the
Noise Audiogram," The Journal of the Acoustical
Society of America, I, No. 1 (October, 1929),

147-57.

 

49

 

SO

Goldstein, Robert and Cramer, Joan C. "Factors Affecting

Thresholds for Short Tones," Journal Qf Speech
and Hearing Research,III, N0. 3 (September, 1960),
249 56.

Harris, J. Donald. "A Factor Analytic Study of Three
Signal Detection Abilities,” The Journal of Speech
and Hearing Research, VII, No. 1 (March, 1964),
71-78.

Hawkins, J. E. Jr. and Stevens, S. S. "The Masking of Pure
Tones and of Speech by White Noise,” The Journal
of the Acoustical Society of America, XXII, No. 1
(January, 1950), 6413.

 

 

Hinchcliffe, Ronald. "Threshold of Hearing for Random
Noise," Journal of Speech and Hearing Research,
IV, No. 1 (March, 1961), 57-64.

Miller, George A. ”Sensitivity to Changes in the Inten-
sity of White Noise and Its Relation to Masking
and Loudness," The Journal of the Acoustical
Society of America, XIX, No 4 (July, 1947),

659 19.

Montgomery, H. C. I'Influence of Experimental Techniques
on the Measurement of Differential Intensity
Sensitivity of the Ear,” The Journal of the Acous-
tical Society of America, VII, No. 17(July, 1935),

39-43.

Pollack, Irwin. "Discrimination of Sharp Spectral Changes
Within Broadband Noise,‘ Journal of Auditory
Research, III, No. 3 (July, 1963), 24-32.

Schafer, Tillman H. and Gales, Robert S. ”Auditory Mas-
king of Multiple Tones by Random Noise,” The
Journal of the Acoustical Society of America, XXI,

No. 4*(July, 19497, 392-98.

Small, Arnold M., Jr. and Minifie, Fred D. ”Intensive
Differential Sensitivity at Masked Threshold,”
Journal of Speech and Hearinngesearch, IV, No. 2
(June, 1961), 164-71.

 

Tanner, Wilson P., and Swets, J. A., ”A Decision-Making
Theory of Visual Detection,” Psychological Review,
LXI (1954), 401-409.

 

51

Wright, Herbert N. ”Switching Transients and Threshold
Determinations," Journal of Speech and Hearing
Research, I, N0. 1 (March, 1958), 52-60.

Montgomery, H. 0. "Influence of Experimental Techniques
on the Measurement of Differential Intensity
Sensitivity of the Ear,” The Journal of the
Accoustical Society of America, VII, No. 1 (July,

1935), 39-43.

Reports

Peterson, W. W. and Birdsall, T. G. T eor f i nal
Detectibility. Electronic Defense Group Technical
Report No. 13. Ann Arbor, Michigan: The University

of Michigan, 1953).

Tanner, Wilson P., Swets, J. A., and Green, D. M. Some
General Properties of the Hearing Mechanism,
Electronic Defense Group Technical Report No. 30.
Ann Arbor, Michigan: The University of Michigan,

1956.

 

gr

APPENDICES

52

 

APPENDIX A

Equipment used in the study:

Hewlett-Packard Low Frequency Oscillator, Model 202 C
Grason-Stadler Noise Generator, Model 455 B

Ampex Four Channel Mixer-Preamplifier, Catalog
Number 96910-01.

Bruel and Kjaer Electronic Voltmeter, Type 620.
Ampex Model 620 Line Amplifier (2 used)

Telephonics Headphones, Model TDH - 39.

 

53

H

to m F‘ as +4 +4 la H F’ r4 +4 H
HOKOCD'QQU‘IJTWMHO

MK)
WM

(3 (D -< O\ tn tr 0) r0

mmmmmmmmmmmmmmmmmmmmmmm

ZZZZZZZZZZZZZZZZZZZZZZZ

24.
25.
26.
27.
28.
29.
30.
30.
31.
32.
33.
34.
35-
36.
37.
38.
39-
40.
41.
42.
43.
44.
45.

APPENDIX B

Response Form

 

CDC/JCDUJUJ

UJUJUJCDCDUJUJCDCDUJUJCDUJUJUJUJUJU)

ZZZZZZZZZZZZZZZZZZZZZZZ

54

47.
48.
49.
50.
51.
52.
53.
54.
55-
56.
57-
58.
59-
60.
61.
62.
63.
64.
65.
66.
67.
68.
69.

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79.
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93.
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101.
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109.

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110.
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126.

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127.
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2

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ROOE‘A USE ONLY.

 

 

 

MICHIGAN STATE UNIVERSITY LIBRA

1

RIES

3 1293

3

IIIIIII

69 0096

 

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