Children’s Laughter
Running Head: CHILDREN’S LAUGHTER
The Acoustic Features of Children’s Laughter
Katherine Tennis
12 April 2009
Vanderbilt University
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Children’s Laughter
Abstract
Laughter is a unique sound—one that most of us produce many times each day. Despite
laughter’s seeming ubiquity, though, we really do not know much about this vocalization’s
psychological function(s) or details about its acoustics. The goal of the proposed research is to
measure several acoustic features from a large corpus of children’s laughter, with the goal being
to catalog what makes this class of vocalizations arguably special. Through duration and
frequency analyses we predict that due to their comparatively underdeveloped vocal-production
anatomy, children’s laughter will have a much higher F0 than adult laughter and will not expect
sex differences. We also predict that children’s laughter may be more tightly coupled to internal
emotional state seems to be the case for adult laughter.
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Children’s Laughter
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The Acoustic Features of Children’s Laughter
Laughter is a unique sound with varying theories as to its psychological functions.
Currently, there are two primary competing theories about the psychological function of
laughter. The first of these assumes that laughter is a veridical indicator of one’s emotional state.
Thus when we laugh, it is because we are feeling happy or joyous. This perspective has received
support through arousal studies, where it has been shown that young children laugh in response
to a positive stimulus such as tickling or play with either their mother or a companion (Rothbart,
1973). The competing view specifically avoids this sort of meaning-based approach and instead
posits that laughter is a tool used in social communication to elicit emotions, most often positive
emotions, in others. Analysis of social facilitation of children’s laughter has shown that laughter
of a participant can induce laughter in their partner (Chapman, 1973), showing elicitation of
happiness and supporting this second perspective.
The source-filter theory is used to study speech production and has also been used to
study laugh sounds (e.g., Bachorowski, Smoski, & Owren, 2001). In this theory, sound is the
combination of source energy and filtering effects. Source energy describes the function of the
vocal folds in the production of sound. When we are laughing, air is expelled from our lungs up
through the larynx, which contains the vocal folds. This movement of air causes quasi-periodic
vocal fold vibration, which gives rise to a fundamental frequency (i.e., F0, which is highly
correlated with the perception of pitch). The length and mass of the vocal folds constrain F0. For
example, males have longer and more massive vocal folds and thus they vibrate at a lower F0.
Listeners, in turn, hear sounds with a comparatively low pitch. Women have shorter and less
massive vocal folds, which vibrate at a correspondingly higher rate and are therefore perceived
Children’s Laughter
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by listeners as having a higher pitch. Children have still shorter and less massive vocal folds,
resulting in sounds with an even higher F0.
Filtering effects are used to refer to the shaping of energy as it passes through the
supralaryngeal vocal tract, including the mouth and nasal passages. These filtering effects give
rise to a number of acoustic aspects, including the specific sound being produced as well as
idiosyncratic cues to the individual sex and identity of the vocalizer. Some research has
examined whether laughs are also individually distinctive, but to date the results are inconclusive
(Bachorowski et al., 2001).
Given the ubiquity of human laughter, it is surprising that so little is known about either
its acoustics or its function. Even less is known about children’s laughter. Most studies of
children’s laughter have focused on psychological functions rather than its acoustics (Foot et. al.,
1977; Otta & Sarra, 2001). Those studies that have looked specifically at acoustics have very
small sample sizes—fewer than 10 subjects—so it is difficult to know the extent to which these
findings are generalizable. However, these studies are useful as a source of comparison.
Bachorowski et al.’s (2001) analysis is one of the few papers that explore details about the
acoustic features of laughter. Although their work focused on the laughter of young adults, the
research served as a model for the research described here. In the study with college-aged adults,
laugh bouts produced by 97 adults as they watched humorous videos were analyzed for their
overall acoustic quality, duration, F0-related measures, and vocal-tract filtering effects. One of
the most salient outcomes was that laughter was found to be highly variable with respect to its
acoustics, especially in comparison to typical speech. Durations of both bouts and calls were
highly variable between participants and within the laughs themselves. Also it noted were that
laughs were temporally unique from speech in that “average sound-production rates are faster in
Children’s Laughter
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laughter than in conversational speech” (p. 1592). F0-related measures were also highly variable.
Interestingly, it was found that there was a connection between F0 and duration of a laugh.
Analysis showed that “long bouts were associated with both higher mean F0 and greater F0
variability than were shorter ones” (p. 1593-1594). Spectral outcomes were also analyzed by
measuring formant frequencies. Contrary to past speculation, it was found that most voiced
laughter did not contain articulated vowel-like sounds, such as “hee” and “ho” but rather that
laughter sounds are formed with central vowel sounds. It will be interesting to see if this
neutrality is duplicated in children’s laughter.
Nwokah, Hsu, and Fogel (1993) looked specifically at the acoustics of children’s
laughter. Laughs from four children were recorded as the participants interacted with their
mother in a playful environment. The investigators conclude that there are four types of laughter
found among children—comment laughter, chuckle laughter, rhythmical laughter, and squeal
laughter. Each has its own specific average frequency and acoustic features. After examining the
recordings from each session, the experimenters found that children produced sounds with high
frequencies reaching into the range of adult female laughter, around 400-500 Hz (Nwokah et al.,
1993). These results highlight the range of children’s laughter in that they are able to produce
vocal sounds at a much higher frequency that most adult females. Also, squeal laughter, which is
a feature purportedly distinct to children’s laughter, was found to have an average F0 of 2000 Hz
(Nwokah et al., 1993). The main finding from this study is that children’s laughter is fairly
distinct from adult laughter in that it typically has a higher frequency. Adult female laughter has
been found to have a mean F0 of 415Hz with a standard deviation of 193 (Bachorowski et al.,
2001).
Children’s Laughter
The goal of my Honor’s research was to analyze the acoustic features of children’s
laughter using more acoustic measures and a much larger sample size than had previously been
conducted. The knowledge we have gained in regards to adult laughter will serve as a point of
comparison.
Method
Participants
The participants in this study consisted of 150 8-9 year old children (75 female) and 150
16-17 year old adolescents, all of whom were recruited from the greater Nashville area.
Participants were recruited from announcements in the Vanderbilt Register, on the Kennedy
Center Website, and with pamphlets placed in Pediatric and Adolescent Medicine clinics and
youth organizations. The participants were tested in pairs comprised of same- or different-sex
friends or strangers.. For the purposes of this study I only used data from the prepubescent
children. The overarching goal of the study is to test whether reported sex differences in the use
of laughter emerge with biological maturity (see Bachorowski, Smoski, Tomarken, & Owren,
2009). In this study 58 of the total 150 participants, 34 males and 24 females, were examined.
Materials
Each participant completed four self-report questionnaires: the McGill Friendship
Questionnaire-RA, which was modified for use in this study; a “Game Rating” Questionnaire
that utilizes a 6-point Likert scale to assess enjoyment of a particular task; a Biological Maturity
Questionnaire based on Tanner stages of maturation, which was completed by parents; and a
Demographic form, which was also completed by parents. None of these measures were
examined for the present report.
Design and Procedure
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Children’s Laughter
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Interested parents or guardians were asked to call the laboratory at which time a
residential address was obtained and informational and consent packets were sent. If the
participant was assigned to be in a friendship dyad, the parent/guardian was requested to select a
friend of their child for testing, and that child’s parent/guardian was also sent informational and
consent packets.
Testing took place in the Vocal Communication Laboratory at Vanderbilt University.
When they arrived at the testing site, participants were seated with their partner (i.e., either a
same- or other-sex friend or stranger) at a large table in a comfortably furnished room. Both
participants were asked to give oral and written consent for recording audio and video data. They
were told that the purpose of the study was to examine vocal communication, including laughter,
produced by people as they interact with each other.
After consent was provided participants were seated in comfortable futon chairs 129.5cm
apart with a footstool placed 35.5cm in front of both chairs, providing a workstation, in the same
laboratory room. Thirty-four participants wore a wireless microphone (Audio-Technica
Transmitter, ATW-T51; Stow, Ohio) clipped to the participant’s clothing 5-7.5cm away from the
chin. The audio signal was transmitted to a corresponding receiver (Audio-Technica, ATWR1451 UHF Diversity Receivers; Stow, Ohio) located in the control room. However, when the
microphones were clipped to the participant’s shirts, significant crossover between audio signals
of the other participant was evident. From this point forth, participants wore headworn
microphones (n=126 participants; Audio-Technica PRO 8HE; Stow, Ohio) until headsets for
wireless microphones became available (n=140; Audio-Technica Headset, ATM-75; Stow Ohio).
Audio signals from both the wireless and headworn microphones were sent to an amplifier
(Applied Research Technology, Dual Channel Tube Microphone 254; Rochester, NY) and
Children’s Laughter
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recorded by digital tape (Panasonic Professional DAT receiver, SV-4100, Los Angeles, CA) for
the first 150 participants, which was done to facilitate acoustical analysis. For the other 150
participants the signal was sent to a CD recorder (Superscope Technologies PSD300 CD
Recording System; Aurora, Illinois), which eliminated the need for subsequent signal
digitization.
Participants were also videotaped to associate facial expressions and body movements
with their laughter. This was accomplished with the use of two JVC palm-sized camcorders
(VHS-C Compact GR-AX710, VHS-C Compact GR-AXM255; Wayne, NJ). The video was sent
to a digital AV mixer (Panasonic WJ-AVE55; Secaucus, NJ), which organized the images and
transmitted the signal to a videocassette recorder (Panasonic AG-5700; Secaucus, NJ), recording
the images to videotape.
Once the audio and video devices were set up, the researcher began the study proper. The
researcher taught the participants how to step their way through twelve interactive games.
Participants were instructed to take turns reading instructions to one another and then followed
the given instructions. The cards providing instructions for each task consisted of a deck of
twelve numbered cards positioned on the footstool between the two participants. The cards were
presented in two orders to control for order effects. Six of the tasks involved conversational
items while the remaining six involved humorous items. The tasks were selected so that some
(n=9) could be used with both age groups. Many of the tasks involved props such as Whoopee
cushions, paper, crayons, and Scrabble letters. These props were kept in an easily accessible cart
placed next to the participant’s chairs. Participants were instructed to play the game for the
entirety of a three-minute timer and to stop that game and move on to the next when the time ran
out.
Children’s Laughter
9
After an explanation of the task, the researcher left the room to adjust the input level of
the preamplifier and asked the participant to count to ten in a normal voice. The researcher then
returned to the room to give final reminders and tell the participants that they may ask questions
at any time. Participants were monitored from the adjacent control room via headphones (Tandy
Optimus LV-20; Fort Worth, TX) attached to a DAT or CD recorder. If it was necessary,
researchers could communicate with participants using a wireless intercom (Radio Shack Tandy
Automatic, 43-227; Forth Worth, TX). Once the recorders were started, the participants were
told to begin and the researcher left the room until all twelve tasks were completed.
At this time, the parents or guardians of the participants were asked to complete the
Biological Maturity Questionnaire and the Demographic Questionnaire. If the parent was not
present at this time, these forms were then mailed to the person who provided consent for
participation.
Upon completion of the twelve tasks, each participant was escorted to a separate room
and asked to complete the modified McGill Friendship Questionnaire-RA and the Game Rating
form. Participants were then debriefed, provided $10 as compensation for their time, and thanked
for their participation.
Laugh Selection, classification, and acoustic analysis
More than 15,000 laughs were produced in this study. Laughter was defined as an audible
sound that any person would describe as a laugh in a normal circumstance (Bachorowski et al.,
2001). In order to be selected for acoustic analysis, each laugh bout had to consist of two or more
calls, produced independent of speech, and in the absence of acoustic crosstalk from the second
participant.
Children’s Laughter 10
Using terminology from acoustic primatology (e.g., Struhsaker, 1967; Owren, Seyfarth,
and Cheney, 1997), laughs were analyzed at the “bout” and “call” levels. Bouts are entire laugh
episodes. Exhalations and inhalations were included if deemed critical to the integrity of the
laugh. Calls are discrete acoustical units of bouts; otherwise known as laugh syllables or notes.
Laughs requiring digitization were digitized at 50kHz with Kay elemetric’s computerized
speech lab (CSL; Lincoln Park, NJ). Acoustic analyses were conducted using ESPS/WAVES+
5.2 digital signal-processing software (Entropic Research Lab, Washington, DC), which was
implemented on a Silicon Graphics O2 unix-based processor with the Irix 6.3 operating system
(SGIL; Mountain View, CA). Preprocessing of files included format conversions on a personal
computer using custom-written software programs by Tice and Carrell (available at
http://hush.unl.edu/LabResources.html). Files were then down-sampled to 11.025kHz and
normalized to a common maximum-amplitude value.
Each three-minute file was segmented with offset and onset markers at the bout and call
levels. Both levels were then categorized by type. Bouts and calls consisting of mostly “songlike” sounds with evident F0 were labeled as “voiced.” Bouts and calls consisting of mostly
noisy, non-periodic vocal fold vibrations were labeled as “unvoiced.”
Duration measurements were extracted from offset and onset markers. F0 analyses were
performed at the call level using ESPS/WAVES+ pitch-tracking routine to extract the F0 contour
and then overlay the resulting plot on the corresponding narrow band spectrogram. However, this
native pitch-tracking algorithm did not always perform well as the F0 of children’s laughter is
especially high and variable. When the algorithm failed, the first harmonic was manually
enclosed in both frequency and time via cursor settings. Its F0 contour was then extracted using
maximum-amplitude points occurring one per column in the underlying spectrogram.
Children’s Laughter 11
We attempted to analyze formant frequencies by deriving them from smooth spectral
envelopes produced through linear predictive coding (LPC). First, a narrow band FFT-based (40ms Hanning window, 0.94 preemphasis factor, 512-point FFT, 2-ms step size) and a wideband,
LPC-based (fast modified Burg method, 40-ms rectangular window, 0.94 preemphasis factor, 10
coefficients, 2-ms step size) spectrogram of each sound were produced. Theoretically, one
location would then be designated within the voiced call or segments that would provide clear
outcomes that are representative of the sound as a whole. However due to the very high F0s
associated with qualities of the children’s laughter, we were unable to reliably measure formants
as these were indistinguishable from the harmonics, or integer multiples of F0.
Results
Bout-level descriptive outcomes.
Descriptive outcomes associated with bout-level analysis are shown in Table 1, and
representative spectrograms of voiced and unvoiced laughter are shown in Fig. 2 and Fig. 3,
respectively.
Table I.
a) Bout Level
Total Laughs (n)
M Duration
Bout type
Males producing (%)
Total Bouts (%)
Males (n=34)
467
1.21 (1.13)
Voiced
Unvoiced
77
79
76
24
M Duration (s)
1.18 (1.09)
1.33 (1.24)
Females (n=24)
497
1.11 (0.92)
Voiced
Unvoiced
Total (n)
M Duration
Bout type
Females producing
(%)
% of Total Bouts
M Duration (s)
100
80
1.03 (0.78)
74
20
1.44 (1.30)
Children’s Laughter 12
Fig. 2 Voiced Laughter
Fig. 3 Unvoiced Laughter
A total of 964 bouts were analyzed, and of these, 78% were predominantly voiced and
22% were predominantly unvoiced. The majority of participants produced both types of laughs
with 86% of participants producing voiced bouts and 75% producing unvoiced bouts.
Laugh bouts were highly variable in duration, with a standard deviation of 1.02
associated with a mean of 1.16 s. This next sentence talks about two results but only has 1 F
value. On average, laugher sex did not affect the type of bout produced F(1,963)=2.827, ns. Male
and female participants also did not differ in mean bout duration F(1, 41)= 0.000, ns, or in the
standard deviation of bout duration F(1,41)= 1.215, ns.
Call-level descriptive outcomes.
A total of 4806 calls were analyzed and descriptive outcomes are shown in Table 2.
Children’s Laughter 13
Table 2.
Call Level
M Calls per bout
M Duration (s)
Call type
% Males producing
% of Total calls
M Duration (s)
M Calls per bout
M Duration (s)
Call type
% Females producing
% of Total calls
M Duration (s)
Males (n=34)
5.37 (4.36)
0.13 (0.11)
Voiced
Unvoiced
88
94
72
28
0.11
(0.078)
0.19 (0.15)
Females (n=24)
4.89 (3.27)
0.147 (.109)
Voiced
Unvoiced
100
100
72
28
0.13 (0.96)
0.19 (0.13)
On average laugh bouts were composed of 5.09 calls with a standard deviation of 3.82, showing
that there is high variability in the number of calls produced per unit of laughter. The majority of
calls were voiced (72%), with the remaining 28% of calls classified as unvoiced. Call durations
were highly variable with a standard deviation of 0.11 associated with a mean duration of 0.13 s.
Call duration was significantly associated with the type of call produced F(1, 4805)=376.9,
p<0.05. Specifically, unvoiced calls were longer than voiced versions. Call durations were also
significantly associated with laugher sex F(1, 55)= 7.291, p<0.05, with females producing longer
calls than males. However, the standard deviation of call durations was not associated with
laugher sex, F(1,55)=0.979, ns, nor did laugher sex have an influence on the type of call
produced F(1, 4804)=0.000, ns.
F0 –related outcomes.
Descriptive analysis associated with F0 –related outcomes are shown in Table 3.
Children’s Laughter 14
Table 3.
Measures (Hz)
M F0
s.d. F0
F0-Excursion
Males (n=31)
Females (n=24)
417 (62.9)
26.3 (22.5)
56.8 (56.5)
426 (46.7)
30.5 (24.4)
69.2 (65.8)
Participants (n=55)
Measures (Hz)
M F0
s.d. F0
F0-Excursion
396 (61.5)
28.4 (23.5)
63.0 (61.7)
F0 analysis could be performed on 3269 voiced calls, or roughly 94% of all voiced calls.
The ESP/WAVES + program was used to analyze roughly 60% of the calls analyzed, while the
remaining calls were analyzed by extracting the maximum-amplitude points from the first
harmonic. Three measurements were of particular interest: mean F0 , SD F0 , and F0 –excursion
[(maximum call F0)–(minimum call F0)].
Mean F0 did not differ significantly based on laugher sex, F(1,35)= 0.416, ns, nor did its
standard deviation, F(1,35)=0.210 ns. Surprisingly, there was a significant difference between
the absolute maximum F0 values for males and females, with females presenting a maximum of
2326Hz and males presenting a maximum of 3316Hz. Interestingly, male laughers presented a
higher absolute-maximum than females.
Standard deviations of within-call F0 s were quite high, with males and females having
mean standard deviations of 26.3 (22.5) and 30.5 (24.4), respectively. However, these outcomes
were not statistically different from each other, F(1,49)=1.260, ns. Mean F0 –excursion was large
for both sexes (Mmale=56.8, s.d.=56.5; Mfemale=69.2, s.d.=65.8). However, there were no
significant differences based on sex in mean F0 –excursion, F(1,49)=0.005, ns, nor in standard
deviation for F0 –excursion, F(1,49)=0.064, ns.
Children’s Laughter 15
Discussion
This study provides a preliminary look at the acoustics of children’s laughter—a subject
that until recently has not been explored in any degree of detail. What is most notable about the
findings of this study are the vast differences between children’s and adult’s laughter and the
lack of differences based on laugher sex.
A comparison of the acoustic data of children’s laughter with that of adult laughter gives
insight into the role of biological maturation in the production of laughter. Due to anatomical
differences on vocal-fold that occur during puberty, sex differences are much more pronounced
in adult laughter. Not unexpectedly, adult female mean F0 was considerably higher and more
variable than adult males (Bachorowski et al., 2001). This finding was not replicated when
analyzing the acoustics of children’s laughter. Additionally, female adult laughter was found to
have a higher absolute maximum F0 than males, which was also not found to be the case in
children’s laughter. To the contrary, pre-pubescent boys showed higher F0 maxima than
prepubescent girls. Additionally, male adult laughers produce significantly less voiced laughs
than females (Bachorowski et al., 2001). However, in children’s laughter, it was found that both
male and female laughers produce more voiced than unvoiced laughter. The lack of sex
differences in children’s laughter implies that children do not possess the dimorphism in vocalproduction anatomy to support the sex differences observed in adults. The results also imply that
pre-pubescent children are not subjected to the same sexual pressures that adult males and
females are, and thus are less inclined to use their laughter as adaptive responses to such
pressures. It has been supposed that adult females use voiced, song-like laughter to elicit positive
emotional stances in men (Bachorowski et. al., 2001). Thus adults, at least in part, appear to use
their laughter as a social tool to elicit positive emotions from others, resulting in sex differences
Children’s Laughter 16
that are reinforced by societal and sexual pressures. To date, this does not appear to be the case
in children’s laughter, suggesting that children are not subjected to the same pressures and thus
do not rely on laughter as a tool of social influence. Instead, these findings are consistent with
the notion that children’s laughter is more tightly coupled with internal affective state than is
adult laughter. This idea will be explored by examining the links between self-reported
enjoyment of the games and the amounts and kinds of laughs produced during each.
Studies of children’s speech have provided mixed evidence for the average age at which
sex differences in F0 emerge. While it is known that male adults have longer vocal tracts than
female adults (Fitch and Geid, 1999), this difference does not emerge until puberty, suggesting
that some differences seen in boys and girls speech can be due to behavioral reasons rather than
anatomical ones. It has been shown that males and females will alter their voices unnaturally to
become lower and higher, respectively, to conform to societal ideals (Sachs, Lieberman, and
Erikson, 1973). Thus differences in speech between the sexes only seem to anatomically emerge
during puberty with the “descent of the larynx” in males (Fitch and Geid, 1999). The finding that
sex differences are not present in prepubescent speech has been replicated in several studies
(Murphy, 1964; Luchsinger and Arnold, 1965; Kaplan, 1971). For this reason, we did not expect
to find notable differences in laughter for 8-9 year old children. Interestingly, it was found that
male children have a larger absolute maximum F0 than female children laughers. While it was
predicted that females would have a higher maximum F0 due to anatomical differences, others
have found that young males have a higher absolute maximum F0 in modal speech (Sachs, et al,
1973). Predictably, children’s laughter had a much higher mean F0 (Mmales=366, sd=62.9;
Mfemales=426, sd=46.7) than children’s speech, reported as 230.4Hz with a standard deviation of
13.1 for males and 246.7Hz with a standard deviation of 22.4 for females (Hasek, Singh, &
Children’s Laughter 17
Murry 1980), for 8-9 year olds. Female laughter was found to be more variable than that of
males, a finding that is replicated in studies of adult laughter.
Conclusion
The data considered here indicates that the acoustics of children’s laughter are not only
highly variable but also differ considerably from children’s speech. Additionally, the findings of
this study show that the acoustics of children’s laughter differs significantly from that of adult
laughter, specifically in F0 measures and sex differences. These acoustic differences to adult
laughter indicate that the purpose of children’s laughter may differ from that of adults.
Specifically, these suggest that the function of children’s laughter may be more likely linked to
the child’s internal emotive state rather than social communication. A difference in function
based on age shows that laughter seems to be an acoustic function that matures over time due to
exposure to biological and social pressures. Further work on this project would focus on
completing analysis on all of the data collected during the original study. Exploration of the
arousal hypothesis of the function of laughter should be further explored through a comparison
between self-report surveys of enjoyment and number of laughs produced per game. Also,
statistical testing should be done to analyze the potential differences in vocal production between
prop and non-prop games, which would help to distinguish “play ground” laughter from
conversational laughter, respectively.
Children’s Laughter 18
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