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The V oice

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The Voice of Deceit Refining and

Expanding Vocal Cues to Deception

Patricia Rockwell David B. Buller

University of Southwestern Louisiana AMC Cancer Research Center

Judee

K.

Burgoon

University of Arizona

TTH'S study examined

the

nature

of

deceptive vocal behavior

in

interactive

situations. Data from

an

earlier study were used

to

conduct

a

detailed analysis

of vocal features

of

deceptive speech. Vocal samples were analyzed perceptually

and acoustically.

Of

three categories examined (time, frequency,

and

intensity),

the time variables best discriminated between truthful and deceptive speakers,

with deceivers exhibiting shorter message length, longer response latencies,

slower tempo,

and

less fluency than truthtellers. Deceivers also evidenced

increased intensity range, increased pitch variance,

and

less pleasant vocal

quality than truthtellers.

Vocal behavior has been found to be a major factor in discriminating between

deceptive and truthful speakers (DePaulo, Stone, Lassiter, 1985; deTurck & Miller, 1985;

Zuckerman, DePaulo, Rosenthal, 1981). However, the findings regarding individual

components of deceptive voices have not always been consistent across studies (Cody,

Marston, Foster, 1984; Matarazzo, Wiens, Jackson, Manaugh, 1970; Motley, 1974;

Patricia Rockwell

(Ph.D.,University of Arizona, 1994) is an Assistant Professor, Department of

Communication, University of Southwestern Louisiana, Lafayette, LA 70504. David B. Buller

(Ph.D.,Michigan State University, 1984)is a Senior Scientist, AMC Cancer Research Center, Denver,

CO. Judee

K.

Burgoon (Ed.D., West Virginia University, 1974) is a Professor, Department of

Comm unication, University of Arizona, Tucson, AZ 85721. This project w as su pported by the U.S.

Army Research Institute (Contract #MDA903-90-K-0113) and th e

U.S.

Army Research Office (Grant

#30235-RT-A

AS).

T he views, opinions, and findings in this report are those of the authors and should

not be construed as an official Departm ent of the A rmy position, policy, or decision.


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Page 452 -

Communication Research Reports/Fall 1997

O'Hair,

Cody,

McLaughlin, 1981). Some deception studies have used acoustic measures

to

de termine vocal features

(e.g.,

Ekman, CS ulliva n, Friesen, & Scherer,

1991;

M otley, 1974),

but the overwhelming majority have used perceptual measures (e.g., Buller

Aune , 1987;

Buller, Comstock, Aune, & Strzyzew ski, 1989; Buller, Strzyzewski, & C omstock, 1991; Cody

et al, 1984; deTurck & Miller, 1985; Hock ing & Leathers, 1980). Occasionally, decep tion

researchers have used both percep tual and acoustic measures in one study (e.g., an acoustic

measure of fundamental frequency and a perceptual measure of tempo in Zuckerman &

Driver, 1985), but no stud ies could be located that measu red vocal features both acoustically

and perceptually. The pvupose of the present s tudy is to determ ine which vocal behaviors

best discriminate between truthful and deceptive vocal behavior using both acoustic and

perceptual measures.

Vocal behaviors traditionally examined in deception research tend to fall into three

broad categories as delineated by Scherer (1985). They consist of time, frequency, and

intensity.

Time.

Vocal features concerned w ith the length or speed of an utterance, either vocalized

or unvocalized, may be considered a com ponent of time . One consistent finding is that of

shorter overall message duration for deceivers (deTurck & Miller, 1985; Knapp &

Comadena, 1979; Mehrabian,

1971;

Zuckerman & Driver, 1985). The theoretical basis for

expecting shorter messages in deception may stem from the deceiver's reticence to offer

more information than necessary.

A less frequently reported finding is that of slower overall tempo which is a measure

typically derived from a count of the total number of words or syllables in the utterance

com pared to the total time of the utterance . Mehrabian (1971) reported slower tem pos for

deceivers than for truthtellers. The finding of slower tem pos

is

consistent with the argu m ent

that deception increases cognitive difficulty.

Deception researchers regularly report decreased fluency for deceivers (deTurck &

Miller, 1985; Marston, 1920; Matarazzo et al., 1970). One commonly noted deception

disfiuency is the response latency, a pause immediately preceding a deceptive answer

(deTurck

Miller,

1985;

Kraut,

1978;

Matarazzo et al., 1970). These various tim e findings

pro m pt the following h ypotheses:

H I: Com pared to truthtellers, deceivers will exhibit: shorter overall

message duration,

H2:

slower tempos,

H3:

less fluency, and

H4: longer response latencies.

Frequency.

The_most_frequently_ reported finding in deception research regardirig

frequency_is.that deceptive voices increase in general pitch level, or fundam enta l frequency,

w ith most researchers arguing that increased pitch level

is

prom pted by decep tion-induced

arousal (Apple, Streeter, & Kraus, 1979; H ocking & Leathers, 1980; Streeter, Kraus, Geller,

Olson,

Apple,

1977;

Zuckerman

Drive r, 1985).

Despite repeated findings, some researchers believe that other measures of pitch, such

as pitch range or pitch variety, may

be

better indicators of deception than p itch level because


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The

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following hypothesis and research questions regarding frequency are offered:

H5:

Comp ared to truthtellers, deceivers will exhibit high er pitch

levels.

RQ l: Comp ared to truthtellers, will deceivers exhibit less pitch variety?

and

RQ2:

A narrow er pitch range?

Intensity.

Intensity, or loudness, is not studied as often as time and frequency in

deception research (often due to inadequate recording equipment). Mehrabian (1971)

repo rted decreased intensity for deceivers. Buller and A une

(1987)

measured loudness

as

an

aspect of vocal activity and found th at this composite variable increased for deceivers in

certain conditions . Findings from research on emo tion suggest that vocal intensity may

reveal speakers' sincerity or confidence (Alpert, Kurtzberg, &

Friedhoff, 1963;

Frick, 1985;

Kimble & Seidel,

1991;

Scherer, 1978). Even so, it is prem atu re to pred ict the direction or

deg ree of intensity change, so the following research question is presented :

RQ3:

^W hat changgjun intensity are indicative of deceptive behavior?

Other vocal features.

Few other vocal features have been examined as possible cues to

decep tive voices. Thus, it is difficult to hypothesize w hich behav iors may occur. Find ings

outside of the deception literature suggest potential vocal cues to deception. For instance,

research on the vocal features of emo tion have dete rmin ed that articulation (as encoded as

formant frequency) may be associated with perceptions of different emotions (Ross,

Edmondson, & Seibert, 1986; Scherer, 1978; 1992, Scherer & Oshinsky, 1977) with the

emotions of pleasantness, happine ss, and surprise exhibiting more clipped articulation tha n

those of boredom, disgust, and sadness. Deceptive speakers may experience emotions

differently from those they might experience if they were truthful and may expose these

differences in their articulation.

Likewise, vocal quality (comprised of those vocal behaviors moderated by speakers'

physiology such as amount of resonance, breathiness, or nasality) may change during

deception. Scherer

(1985)

claims tha t a less pleasant voice quality may be an excellent cue to

deception because it audibly reflects the vocal tension that may accompany deception-

induced arousal. When a deceiver experiences arousal, the vocal mechanism may und ergo

certain physiological changes such as increased tension of the vocal folds and disrupted

breathing, causing the speake rs' vocal quality to sound less resonant and relaxed, and thus

less pleasant (Scherer, 1978). Therefore, the following research question is posed:

RQ4: W hat other features of the voice, if any, distinguish between

deceivers and truthtellers?

METHOD

Data for the present study w ere dra w n from an earlier stud y (Buller, Burgoon, Buslig, &

Roiger,

1993).

The original project utilized a2 X 3 X 2X 2 factorial design. Variables analyzed


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For the present study, videotapes of speakers telling the truth and lying in response to

interview-type questions were used for coding vocal behaviors. C oders evaluated speakers'

vocal characteristics on seven-point L ikert-type scales, with

1

representing a low level of

a particular feature and

7

representing a high level of a particular feature. Vocal

characteristics analyzed included response latencies (short-long), tempo (slow-fast), fluency

(not fiuent-fluent), internal pauses (few-many) (short-long), pitch level (low-high), pitch

range (narrow-wide), pitch variety (unvaried-varied), intensity level (soft-loud), intensity

range (narrow-wide), intensity variety (unvaried-varied), vocal quality (unpleasant-

pleasan t), and articulatory precision (imprecise-precise).

Coders (n=6) were all junior or senior unde rgrad uates majoring in Com mun ication at a

large southwestern university. Coders received over four hours of training on the vocal

behaviors they were assigned to code, including actual practice in coding vocal behaviors

from other experiments. The audio portions of the videotapes were content-filtered to

prev ent coders from being irvfluenced by the verbal content. Coders wo rked in pairs, w ith

one pair coding time and voice quality, another pair coding pitch and p auses, and a third

pair coding intensity and articulation. Interrater reliabilities were generally high (ranging

from a low of

.85

to a high of

.97),

indicating that coders w ere successful in agreeing on the

features of voices.

The tapes we re then submitted to acoustic analysis using software designed

to

evaluate

characteristics of sound signals.^ Features that were analyzed included total amount of

sound, number of sound segments, number of silent segments, total amount of silence,

duration of the initial pause before each question, fundamental frequency mean (in HZ),

fundamental frequency range (in HZ), fundam ental frequency variance, intensity mean (in

dB.),

intensity range (in

dB.),

and intensity variance.

Also included in both the perceptual and the acoustic analyses were total length and

num ber of syllables in each segment as determ ined by auditory co un t These two measures

were used to determine composite measures of temp o and fluency.

RESULTS

To begin the analysis, intercorrelations w ere ru n on the entire set of acoustic variables

and on the entire set of perceptual variables. An examination of the correlations revealed

high correlations among the acoustic measures of length, total sound, number of sound

segments, total silence, and number of silent segments (r>.48); pitch level, range, and

variance (r>.88); and intensity level, range, and variance (r>.62). This examination also

revealed high correlations among the perceptual measures of tempo, pause number, and

pause length

(r>.44);

pitch level, range, and variance

(r>.84);

and intensity level, rang e, and

variance (r>.86). Alpha reliability tests verified these grouping s.

These group s of variables were then subm itted to multiva riate analysis of variance. In

instances where the analyses produced singular variance-covariance matrices, variables

were removed from the cluster according to their alpha reliability scores, wi th the va riable

exhibiting the lowest alpha reliability score in the cluster being removed first. When the

analysis no longer produced singular variance-covariance matrices, removal of variables

ceased. From the use of

this

criterion, it was d etermined that

the

following grou ps of acoustic

variables could be successfully analyzed together: (1) length, total sound, an d nu mber of


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The Voice of Deceit - Page 455

sound), fluency (number of silent segments/total silence), initial pauses (response

latencies), and fundamental frequency variance were analyzed separately.

These tests also revealed that the following groups of perceptual variables could be

analyzed together:

(1)

intensity level, range, and variance (a =.96), and

(2)

pitch level, range,

and variance ( a =.96).

The

perceptual variables of message length (length minus the p rodu ct

of num ber of pause s and length of pause s), tempo , fluency, voice quality, and articulatory

precision were analyzed separately.

MANOVA was used in instances where vocal behaviors were correlated with one

another as determined by high intercorrelations, high alpha reliability scores, and the

Bartlett test of sphericity. This procedu re pro duc ed significant results for three of the five

MAN OVAs. For those variables tha t did not d emo nstrate high intercorrelations, ANOVAs

we re performed on each variab le separately. For variables with significant un ivariate scores

derived from significant MAN OVAs (two out of

six)

and for those variables that prod uced

significant results from the ANOVAs (seven out of 11), planned comparisons with 1

df

contrasts tested the differences between the truthful answer condition and the deception

answ er condition in order to pro vide answers to Hypothese s 1-5 and Research Questions 1-

4.

When violations of symmetry conditions occurred, as dete rmin ed by the Box-M test for

homogeneity of variance and Mauchly's sphericity test, the Huynh-Feldt correction was

employed to adjust the p value . Results of the planned com parisons for the nine significant

individual measures are reported in Table 1.

,

DISCUSSION

A major goal of the current study was to determine which vocal behaviors best

TABLE 1

Comparison of Significant Vocal Measures in Discriminating Between Truthtellers and Deceivers

Message Length

Number of Sounds

Tempo

Fluency

Response Latency (acoustic)

Response Latency (perceptual)

Pitch Variety

Intensity Range

Vocal Quality

Deception

Mean

1.90

1.70

4.30

4.49

11 1

2.69

24.02

8.68

4.18

Tmth

Mean

3.61

2.32

4.56

4.85

1.33

2.00

21.57

7.33

4.32

F-score

9.37

4.86

7.10

5.35

21.13

13.05

6.99

6.58

5.23

g-value

.005

.015

.012

.028

.000

.001

.013

.015

.029

eta

squared

.11

.18

.19

.15

.41

.30

.18

.18

.14


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discriminated between truthtellers and deceivers. As with p revious deception studies, the

findings of this study were complex and not wholly expected in some respects. Three

categories of vocal behavior (time, frequency, and intensity) wer e cons idered .

The time category revealed the greatest number of significant differences betw een truth

and deception, including shorter messages, fewer so unds , slower tempo , less fiuency, and

longer response latencies for deceivers. These cues refiect the im pact of cognitive difficulty

on deceiver vocal behavior. It seems understandable that deceivers may give shorter

responses because producing longer messages wo uld require greater cognition and perh aps

increase leakage cues. Also, longer messages provide more information from which

receivers m ight jud ge sende r honesty. Thu s, deceivers may op t strategically for reticence

(DePaulo et

al., 1985;

O'Hair et

al., 1981;

Zuckerman

Driver,

1985;

Zuckerman et

al.,

1981)

Slower tempo may

be

an overlooked byp roduct of the increased cogn itive load requ ired

to genera te false information, signal uncertainty , decide which information to divu lge an d

to hide, and adapt to conversational events (Mehrabian, 1971). It may also be a strategic

move by deceivers to manage their image and insure fiuency. From a physiological

perspective, increased arousal may prevent the normal, efficient functioning of the

articulators, forcing speakers to slow down in order to be comprehensible (deTurck &

Miller, 1985).

Certainly, deceivers' lack of fiuency has been a prominent finding in most deception

studies (deTurck & Miller, 1985; Matarazzo et al., 1970; Miller et al., 1983; Zuckerm an &

Driver, 1985). Researchers have argu ed that

as

deceivers work to create lies and experience

unpleasant reactions to deceiving, they may lose control of their normal fiuency (̂ Motley

1974; Zuckerman et

al.,

1981). The large effect sizes noted for both acoustic and perce ptual

measures of response latencies (Table 1) provide a dramatic indication that response

latencies are one of the most telltale indicators of decep tive speech. Researchers (deTurck

Miller, 1985; Kraut, 1978; Matarazzo et al., 1970) argue that longer response latencies

typically noted for deceivers are due to increased cognitive load, allowing deceivers

additional time to prepare successful deceptive answers. Deceivers also may be behaving

strategically when they increase response

latencies,

by seeming to pon der

a

question before

answering.

Unlike many other deception studies, this study did not find increased pitch levels for

deceivers; however, the acoustic analysis showed that deceivers exhibited significantly

more pitch variety than

truthtellers.

This may have occurred because deceivers strategically

increased their pitch variety to create an impression of a norm ally expressive, truthful voice

(Scherer, 1985). Few studie s have considered pitch variety as a discriminator betw een truth

and deceit, and if the present results portray an accurate picture of what deceivers do

vocally, pitch variety may prove to be a better indicator of deceit than pitch level. Indeed ,

reports of increased pitch level in previous deception studies may actually have been

increased pitch variety.

Deceivers showed a wider intensity range than truthtellers at least on the acoustic

measures. Although it

is

possible that deceivers increased their range of loudness values in

order to m ake their voices sound mo re norm ally exp ressive (Scherer, 1978; Scherer &

Oshinsky, 1977), a more logical explanation m ay be that deceivers were not able to control

fiuctuations in intensity because increased arousal caused increased vocal tension and


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The Voice

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Deceivers' voice quality was less pleasant than truthtellers'. Voice quality is far less

controllable than other vocal behaviors typically studied in deception research such as

tempo and response latencies (Scherer et al.,

1985;

Zuckerman et al., 1981) because it is mo re

tied to the physiological make-up of the speaker. Thu s it is more difficult for speakers to

modify than features rnore under the speaker's conscious control such as strength and

length of sound produced. Hence, changes in voice quality may be more likely during

deception than changes in tempo or intensity.

In summa ry, the deceiver's voice reveals mu ch abo ut the deception in progress. This

study represents an attemp t

to

refine and expan d the audito ry p icture of the deceptive voice.

By expanding the number and type of vocal cues measured and the methods of

measurem ent, future studies may m ake this picture even m ore clear. Certainly time cues are

imp ortant, b ut researchers need to mo re carefully exam ine frequency, intensity, and vo ice

quality as well.

NOTES

' Results of a comparison of the perceptual and acoustic methods used in this

study

are

reported

in

Measurement of

deceptive voices:

Comparing

acoustic

and

perceptual data,

pplied Psycholinguistics

(in press).

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