The Temporal Modulation Structure of - Am MIT spezialisierte KI-Forschung

The Temporal Modulation Structure of
Infant-Directed Speech

Victoria Leong1, Marina Kalashnikova2, Denis Burnham2, and Usha Goswami1

1Centre for Neuroscience in Education, Abteilung für Psychologie, University of Cambridge

2The MARCS Institute for Brain, Behaviour and Development, Western Sydney University

Schlüsselwörter: infant-directed speech, Phase, oscillations, Amplitudenmodulation

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ABSTRAKT

The temporal modulation structure of adult-directed speech (ADS) is thought to be encoded
by neuronal oscillations in the auditory cortex that ﬂuctuate at different temporal rates.
Oscillatory activity is thought to phase-align to amplitude modulations in speech at
corresponding rates, thereby supporting parsing of the signal into linguistically relevant units.
The temporal modulation structure of infant-directed speech (IDS) is unexplored. Here we
compare the amplitude modulation (BIN) structure of IDS recorded from mothers speaking,
over three occasions, to their 7-, 9-, and 11-month-old infants, and the same mothers
speaking ADS. Analysis of the modulation spectrum in each case revealed that modulation
energy in the theta band was signiﬁcantly greater in ADS than in IDS, whereas in the delta
band, modulation energy was signiﬁcantly greater for IDS than ADS. Außerdem, Phase
alignment between delta- and theta-band AMs was stronger in IDS compared to ADS. Das
remained the case when IDS and ADS were rate-normalized to control for differences in
speech rate. These data indicate stronger rhythmic synchronization and acoustic temporal
regularity in IDS compared to ADS, structural acoustic differences that may be important for
early language learning.

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Zitat: Leong, V., Kalashnikova, M.,
Burnham, D., & Goswami, U. (2017).
The Temporal Modulation Structure of
Infant-Directed Speech. Open Mind:
Discoveries in Cognitive Science,
1(2), 78–90. https://doi.org/10.1162/
opmi_a_00008

DOI:
https://doi.org/10.1162/opmi_a_00008

Erhalten: 27 April 2016
Akzeptiert: 27 Januar 2017

Konkurrierende Interessen: The authors
declare no competing interests exist.

Korrespondierender Autor:
Usha Goswami
ucg10@cam.ac.uk

Urheberrechte ©: © 2017
Massachusetts Institute of Technology
Veröffentlicht unter Creative Commons
Namensnennung 4.0 International
(CC BY 4.0) Lizenz

Die MIT-Presse

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EINFÜHRUNG

Human speech perception relies in part on neural tracking of the temporal modulation patterns
in speech at different timescales simultaneously: “multi-time resolution processing” (Chait,
Greenberg, Arai, Simon, & Kacke, 2015; Ghitza & Greenberg, 2009; Greenberg, 2006;
Luo & Kacke, 2007; Kacke, 2003). According to multi-time resolution models, cortical
oscillations entrain or phase-align their activity to modulations at corresponding timescales in
the signal, thereby encoding the different energy patterns, and binding the information together
in the ﬁnal speech percept (Ghitza, 2011; Ghitza, Giraud, & Kacke, 2012; Giraud &
Kacke, 2012; Kacke, 2014). Exploration of the temporal characteristics of adult-directed
Rede (ADS) has revealed that accurate oscillatory phase alignment is mediated in part by
amplitude “rise times,” auditory “edges” associated with amplitude (Energie) modulations that
help to specify temporal modulation rates (Gross et al., 2013). Rise times in the theta band
appear to be particularly important for successful speech encoding, as acoustic “landmarks”
(amplitude rise times) in critical band envelopes in the theta range of ADS provide perceptual
markers that are critical for speech intelligibility (Doelling, Arnal, Ghitza, & Kacke, 2014).
When acoustic landmarks in the theta range (in this study, 2–9 Hz) were removed, Rede
became unintelligible, and when artiﬁcial landmarks of uniform height were inserted instead,
the speech became intelligible again. Entsprechend, Doelling et al. argued that auditory “edges”

Modulation Structure of Infant-Directed Speech Leong et al.

(amplitude rise times) in the theta band drive oscillatory activity to track and entrain to speech
at its syllabic rate. Vor allem, all experiments to date have investigated literate adult participants.

Im Gegensatz, in child populations, delta band information appears to be critical for suc-
cessful oscillatory entrainment. Studies of children with poor literacy (developmental dyslexia)
reveal impaired encoding of speech envelopes between 0–2 Hz (Molinaro et al., 2016; Power,
Colling, Mead, Barnes, & Goswami, 2016). Children with dyslexia also show atypical phase
entrainment to rhythmic speech in the delta band, but equivalent entrainment to control chil-
dren in the theta band (Power, Mead, Barnes, & Goswami, 2013). Weiter, studies of oscillatory
entrainment to speech by typically developing children show a signiﬁcant relationship between
theta entrainment and learning to read (Power, Mead, Barnes, & Goswami, 2012). For child
Populationen, daher, it is possible that acoustic information in frequency bands other than
theta may be of equal or even greater importance for speech processing. To explore this pos-
sibility, information about the temporal modulation structure of child-directed speech (CDS)
and infant-directed speech (IDS) is required.

To explore CDS, we recently applied a probabilistic amplitude demodulation approach
to modeling the rhythm patterning in children’s nursery rhymes (z.B., capturing whether they
are iambic or trochaic). We compared its output to that of an engineered modulation ﬁlterbank
Ansatz (Leong, 2012; Leong, Stein, Turner, & Goswami, 2014; Turner, 2010), ultimately
deriving a Spectral-Amplitude Modulation Phase Hierarchy (S-AMPH) Modell (Leong, 2012;
Leong & Goswami, 2015). The S-AMPH modeling demonstrated that English nursery rhymes
contained amplitude modulations in three critical temporal rate bands (corresponding to delta,
theta, and beta/low gamma, for this speech corpus 0.9–2.5 Hz, 2.5–12 Hz, and 12–40 Hz; sehen
(Leong, 2012; Leong & Goswami, 2015). Amplitude modulations in these bands were hier-
archically nested in the nursery rhymes, and phase alignment between the slower amplitude
modulation (BIN) bands (delta and theta) played a key role in the perception of rhythmic pat-
terning (judging whether the nursery rhymes were trochaic or iambic). A strong syllable was
perceived when delta and theta modulation peaks were in alignment. Entsprechend, the strong
rhythmic character and acoustic temporal regularity of spoken nursery rhymes appears to be
inﬂuenced by amplitude modulations in the delta band.

Like nursery rhymes, IDS is a highly rhythmic and temporally regular signal (Fernald
et al., 1989;
Jusczyk, Cutler, & Redanz, 1993). Entsprechend, it is plausible that delta band
information and delta-theta phase alignment may also be important characteristics of IDS.
Infant-directed speech is classically described in terms of its higher pitch and greater pitch
range, slower rate and higher amplitude than ADS, with hyperarticulated vowels (Burnham,
Kitamura, & Vollmer-Conna, 2002; Kuhl et al., 1997). Vowel hyperarticulation in IDS has
been proposed to support phoneme discrimination (Liu, Kuhl, & Tsao, 2003) and word recog-
Nation (Song, Demuth, & Morgan, 2010), while high pitch and greater pitch range capture
infant attention (Fernald & Kuhl, 1987) and facilitate speech segmentation (Thiessen, Hill, &
Saffran, 2005). Neural multi-time resolution models of speech encoding (Giraud & Kacke,
2012) raise the possibility that the temporal modulation hierarchy may also provide acoustic
landmarks that support infant language learning, helping infants to locate word and phrase
boundaries. Currently, the temporal modulation structure of IDS is unexplored. Entsprechend,
here we applied the S-AMPH modelling approach (Leong & Goswami, 2015) to IDS.

The S-AMPH model is a low-dimensional representation of the speech signal (see also
Greenberg & Arai, 2001). The model generates a hierarchical representation of the domi-
nant spectral (acoustic frequency) and temporal (oscillatory rate) modulation patterns in the

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Modulation Structure of Infant-Directed Speech Leong et al.

speech envelope. Amplitude modulation patterns in three temporal rate bands (~delta, theta,
and beta/low gamma) form a three-tier nested hierarchy, thereby preserving AM patterning
across different speaker rates. Annotation of the nursery rhyme (CDS) corpus revealed that
for these nursery rhymes, this AM hierarchy (centered on ~2 Hz, ~5 Hz, and ~20 Hz AMs)
mirrored the linguistic phonological hierarchy of stressed syllables, syllables, and onset-rime
units in the spoken material (Leong & Goswami, 2015). Oscillatory cycles in each AM band
thus supported the identiﬁcation of phonological units of different sizes. The number of bands
and their respective bandwidths used by the S-AMPH were originally determined using
principal component analysis (PCA) dimensionality reduction of original high-dimensional
spectral (29 equivalent rectangular bandwidth [ERB]-spaced frequency channels spanning 100–
7,250 Hz) and temporal (24 modulation channels spanning 0.9–40 Hz) envelope representa-
tionen (Leong, 2012; Leong & Goswami, 2015).

Here we applied the S-AMPH to IDS collected from a sample of 24 mother–infant dyads
bei 7, 9, Und 11 Monate alt, and we also analyzed ADS collected from the same mothers.
While application of the S-AMPH formulae to novel corpora cannot be assumed to identify the
same linguistic units, the methods nevertheless enable comparison of relative speech energy in
delta, theta, and beta/low-gamma bands and AM phase synchronization. We were interested
to see whether natural IDS has a different temporal modulation structure to ADS, and whether
the strength of phase alignment between the different AM bands (delta, theta, beta/low gamma)
might show a different patterning in IDS as compared to ADS.

METHODEN

Teilnehmer

Twenty-four mother-infant dyads (9 männlich, 15 female infants) participated in the study.1 None
of the families had any history of language or cognitive disorders. All mothers spoke Australian
English as their native language, and had normal (not > 0.5 SDs below the mean) nonverbal
IQ on a combined subtest score averaging block design and matrix reasoning subscales of
the Wechsler Adult Intelligence Scale IV (WAIS-IV; Wechsler, 2008) (M = 12.2, SD = 2.0,
compared with the population mean, 10.0, and SD, 3.0).

Design and Experimental Setup

There were four speaking conditions, three IDS, and one ADS. Infant-directed speech sam-
ples were collected longitudinally at three time-points, when the infants were 7 (Durchschnittsalter =
31 weeks, SD = 1.1), 9 (Durchschnittsalter = 40 weeks, SD = 1.2), Und 11 (Durchschnittsalter = 48 weeks,
SD = 1.2) Monate alt. Mothers were told that the purpose of the experiment was to cap-
ture their natural interactions with their infants during a brief play session and soft toys and
pictures were provided. Mothers were asked to talk to their infants for as long as they felt
appropriate. All mothers and infants were observed to be motivated and engaged in the task.
Mother and infant interacted alone in a laboratory room. The mother sat facing the infant,
who was sitting in a highchair. A video camera was mounted in each corner of the room to
allow for monitoring and video recording of the session, but only the audio data are analyzed
Hier. The mother wore a head-mounted microphone (AudioTechnica AT892), connected to
Adobe Audition CS6 software via an audio input/output device (MOTU Ultralite MK3). Speech
samples were digitally recorded at 16 kHz (or at 44.1 kHz and resampled to 16 kHz). For the

1 A subset of nine mother-infant dyads also contributed data to an earlier study piloting these analyses (Leong,

Kalashnikova, Burnham, & Goswami, 2014).

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Modulation Structure of Infant-Directed Speech Leong et al.

ADS recordings, each mother interacted with a female experimenter in the laboratory room
using the same recording apparatus, and the infant was not present. Mothers were interviewed
about the experimental play sessions. Adult-directed speech samples were collected when the
infant was approximately 12 months old (mean age: 53 weeks, SD = 8.2). Both IDS and ADS
recording sessions lasted between 5 Und 10 minutes.

Speech Data

The raw audio recordings were manually divided into short segments for analysis using Praat
Software (Boersma & Weenink, 2013). Each segment contained a complete phrase from the
original utterance. Portions of speech that were interrupted by the infant or adult addressee,
or that contained excessive background noise, were not used. In Summe, across the four speak-
ing conditions, mothers contributed 679 speech segments for analysis. On average, segments
were 9.13s in length (range 5.02s–16.92s), and mothers contributed an average of 7.8, 7.9, Und
7.1 segments at the infant ages of 7, 9, Und 11 months, jeweils. Mothers contributed
on average 6.1 segments in ADS. The mean length of speech segments for the different
speaking conditions was 9.2s (7 months IDS), 9.5S (9 months IDS), 9.1S (11 months IDS),
and 8.7s (ADS).

Speech Analysis Method

Each speech segment was
Schritt 1: The S-AMPH Representation of the Amplitude Envelope
z-scored (to standardize its mean and standard deviation), and a low-dimensional spectro-
temporal model (d.h., S-AMPH) of its amplitude envelope was extracted using a two-stage
ﬁltering process, as described in Leong (2012) and Leong and Goswami 2015. Erste, Die
z-scored acoustic signal was band-pass ﬁltered into ﬁve frequency bands (channel edge fre-
quencies: 100, 300, 700, 1,750, 3,900, Und 7,250 Hz) using a series of adjacent ﬁnite impulse
response (FIR) ﬁlters. Nächste, the Hilbert envelope was extracted from each band-ﬁltered signal
and these ﬁve Hilbert envelopes were down-sampled to 1,050 Hz and passed through a second
series of band-pass ﬁlters to isolate the three different AM bands within the envelope
modulation spectrum.
These three AM bands corresponded to delta rate modulations
(0.9–2.5 Hz), theta rate modulations (2.5–12 Hz) and beta/low-gamma rate modulations,
jeweils (12–40 Hz). The result of this two-step ﬁltering process was a 5 (frequency) X
3 (rate) spectro-temporal representation of the speech envelope, described as comprising
delta-,
theta-, and beta/low gamma-rate AM bands for each of the ﬁve spectral bands
(Leong & Goswami, 2015).

Schritt 2: Multi-timescale Synchronization Measure: Phase Synchronization Index (PSI) Nächste, a mea-
sure of multi-timescale phase synchronization, the Phase Synchronization Index (PSI), War
computed between adjacent modulation rate bands in the S-AMPH representation of each
speech segment (d.h., delta-theta phase synchronization and theta-beta/low-gamma phase syn-
chronization). This PSI computation was performed separately for each of the ﬁve spectral
bands in the S-AMPH representation. The n : m PSI was originally conceptualized to quantify
phase synchronization between two oscillators of different frequencies (z.B., muscle activity;
Tass et al., 1998), and was subsequently adapted for use in neural analyses of oscillatory
phase-locking (z.B., Schack & Weiss, 2005). This adaptation is applied to speech AMs in our
Modell. The PSI was computed as:

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PSI = |(cid:2)e1(nθ

−mθ

)(cid:3)|

(1)

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Modulation Structure of Infant-Directed Speech Leong et al.

Figur 1. Hypothetical amplitude modulation (BIN) pairs (sinusoids) that yield Phase Synchroniza-
tion Index (PSI) scores of 1 (links) Und 0.07 (Rechts), jeweils. The red and blue curves represent
AMs with a frequency ratio of 1:2.

In Equation 1, n and m are integers describing the frequency relationship between the two
AMs being compared. Following previous studies (Leong & Goswami, 2014, 2016; Leong,
Stein, et al., 2014), for the delta-theta AM band analysis, an n : m ratio of 2:1 was used, while
for the theta-beta/low-gamma AM band analysis, an n : m ratio of 3:1 was used. The values
θ1 and θ2 refer to the instantaneous phase of the two AMs at each point in time. daher,
(nθ1–mθ2) is the generalized phase difference between the two AMs, which was computed
by taking the circular distance (modulus 2π) between the two instantaneous phase angles.
The angled brackets denote averaging of this phase difference over all time-points. The PSI is
the absolute value of this average, and can take values between 0 (no synchronization) Und
1 (perfect synchronization), as illustrated in Figure 1. A sound with a PSI of 1 is perceived as
being perfectly rhythmically regular (a repeating pattern of strong and weak beats), whereas a
sound with a PSI of 0 is perceived as being random in rhythm.

To assess the modulation spectrum of the speech samples, Die
Schritt 3: Modulation Spectrum
sub-band Hilbert envelopes of the stimuli (resulting from stage 1 of the previously-described
S-AMPH decomposition procedure) were individually passed through a modulation FIR ﬁlter-
bank with 24 channels logarithmically spaced between 0.9–40 Hz. For each speech sample,
and each frequency sub-band, the mean power across all modulation channels was computed,
and the relative power difference from this mean was computed for each modulation channel.
Endlich, the differenced modulation power spectrum was averaged across the ﬁve frequency
sub-bands for each speech sample, and this grand average was used for statistical analysis.

Control Analysis With Rate-Normalized Data

The speaking rate of IDS was slower than that of ADS. As this could introduce potential con-
founds, a rate-normalization procedure was also performed, rescaling the IDS data samples to
the same temporal rate as the ADS samples. Erste, each IDS and ADS speech sample was man-
ually annotated (by native English speakers) to ascertain the number of syllables and stressed
syllables that it contained. This provided a mean syllable rate and stressed syllable rate per
second for each participant in each speaking condition. For each IDS condition, and for each
participant, a scaling factor was then computed based on the ratio between their stressed sylla-
ble rate in the ADS condition, and their stressed syllable rate in the IDS conditions. This scaling
factor was then used to resample each IDS utterance to the appropriate length for that speaker
(z.B., if the stress rate for IDS was half that of ADS, then the IDS sample was compressed so
that it was half of its original length). Identical signal processing steps and statistical analyses
were then conducted with the rescaled data.

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Modulation Structure of Infant-Directed Speech Leong et al.

RESULT

Natural Speech

Figur 2 (panel a) shows the mean modulation spectrum of the speech
Modulation Spectrum
amplitude envelope for each speaking condition. Compared to ADS, the modulation spec-
trum of IDS contained more energy in the delta band (0.9–2.5 Hz), whereas the modulation
spectrum of ADS showed the typical proﬁle of most energy in the theta band, as previously
reported (Greenberg, Carvey, Hitchcock, & Chang, 2003). To assess whether these differences
were statistically signiﬁcant, the area under the curve corresponding to the three modulation
bands was computed (shown in Figure 2, panel b) and assessed using a repeated measures
ANOVA with modulation rate (three levels) and speaking condition (four levels) as within-
subjects factors. There was a signiﬁcant interaction between Rate and Condition, F(6, 138) =
7.78, P < .0001, showing that the relative amount of modulation energy in the delta, theta and beta/low-gamma bands differed between IDS and ADS. Tukey post-hoc analysis revealed that all three IDS conditions contained signiﬁcantly more modulation energy than ADS in the delta band (p < .05 for all). Conversely, for the theta band, ADS contained signiﬁcantly more modulation energy than IDS at 7 and 9 months (p < .05 for both), but not at 11 months (p = .059). In the beta/low-gamma band, ADS contained signiﬁcantly more modulation energy than 9- and 11-month IDS (p < .05 for both) but did not differ from 7-month IDS ( p = .81). Finally, modulation energy did not differ between the three IDS conditions for any AM band (p > .93 for all).

the phase synchronization between AM bands in the
Phase Synchronization (PSI) Nächste,
mothers’ IDS was assessed using the PSI between pairs of AM bands in the S-AMPH repre-
sentation of the speech envelope. Mean PSI values are shown in Figure 3. Each subplot shows
the PSI value (ranging from 0 [no synchronization] Zu 1 [perfect synchronization]) on the y-
axis, and acoustic frequency on the x-axis. The ﬁgure shows more synchronization in IDS than
ADS for delta-theta AM band synchronization in low-frequency spectral bands (100–300 Hz
and 300–700 Hz), but less synchronization for theta-beta/low-gamma AM bands. Darüber hinaus,
for delta-theta band phase synchronization in the middle spectral frequency band (700–
1,950 Hz), typically corresponding to vocalic energy, PSI values increase with increasing age
of the addressee (7M < 9m < 11m < ADS). To compare the conditions statistically, two repeated measures ANOVAs were performed, taking either delta-theta band PSIs or theta-beta/low-gamma band PSIs as the dependent vari- able. In each ANOVA, speaking condition (four levels) and spectral frequency band (ﬁve levels) were the within-subjects factors. For the delta-theta band ANOVA, there were signiﬁcant main effects of Condition, F(3, 69) = 3.07, p < .05, and Spectral Band, F(4, 92) = 27.76, p < .001. The interaction between Condition and Spectral Band was also signiﬁcant, F(12, 276) = 17.92, p < .001. Post-hoc analysis (Newman-Keuls) indicated that for the two lowest spec- tral frequency bands (100–300 Hz; 300–700 Hz), PSI scores for all three IDS conditions were signiﬁcantly higher than for ADS (p < .01 for all comparisons). By contrast, for the middle and highest spectral frequency bands (700–1,950 Hz; 3,900–7,250 Hz), PSI scores for all IDS conditions were signiﬁcantly lower than for ADS (p < .05 for all comparisons). The PSI scores for the 1,950–3,950 spectral frequency band did not differ between IDS and ADS. Finally, for the middle spectral frequency band (700–1,750 Hz), there was a graded effect between IDS at the different ages. Delta-theta AM band phase synchronization in IDS to 7-month-olds was lower (less synchronized) than in IDS to 11-month-olds (p < .05). However, it did not differ OPEN MIND: Discoveries in Cognitive Science 83 l D o w n o a d e d f r o m h t t p : / / d i r e c t . m i t . / e d u o p m i / l a r t i c e - p d f / / / / / 1 2 7 8 1 8 6 8 2 8 2 o p m _ a _ 0 0 0 0 8 p d . i f b y g u e s t t o n 0 7 S e p e m b e r 2 0 2 3 Modulation Structure of Infant-Directed Speech Leong et al. l D o w n o a d e d f r o m h t t p : / / d i r e c t . m i t . / e d u o p m i / l a r t i c e - p d f / / / / / 1 2 7 8 1 8 6 8 2 8 2 o p m _ a _ 0 0 0 0 8 p d . i f b y g u e s t t o n 0 7 S e p e m b e r 2 0 2 3 Figure 2. Panel (a). Mean modulation spectrum for infant-directed speech (IDS) (“07,” “09,” and “11” months) and adult-directed speech (ADS) (“Ad”) conditions, computed for each of ﬁve spectral frequency bands (100–300 Hz; 300–700 Hz; 700–1,750 Hz; 1,750–3,900 Hz; 3,900–7,250 Hz) and then averaged across bands and speakers. The x-axis shows the modulation rate, and the y-axis the power in dB (normalized with respect to the mean power of each frequency band in each sample). Vertical lines indicate the boundaries used to delineate the area under the curve for Spectral-Amplitude Modulation Phase Hierarchy (S-AMPH) delta-, theta-, and beta/low-gamma-rate amplitude modulation (AM) bands. Panel (b). Area under the curve computed for the modulation spectrum in the delta, theta, and beta/low-gamma ranges for each speaking condition (“7” = 7 month IDS, “9” = 9 month IDS, “11” = 11 month IDS, “Ad” = ADS). Note that for the beta/low-gamma range, as the curve falls below zero, the area over the curve is reported instead. Here, a smaller numerical value denotes greater power in the beta/low-gamma range. statistically from delta-theta AM band phase synchronization in IDS to 9-month-olds (p = .14). This suggests that the rhythmic regularity of IDS increases as a function of infant age. For the theta-beta/low-gamma AM band ANOVA, there were again signiﬁcant main effects of Condition, F(3, 69) = 45.84, p < .001, and Spectral Band, F(4, 92) = 119.88, OPEN MIND: Discoveries in Cognitive Science 84 Modulation Structure of Infant-Directed Speech Leong et al. Figure 3. Phase Synchronization Index (PSI) values computed for the delta-theta amplitude mod- ulation (AM) bands (left) and the theta-beta/low-gamma AM bands (right), for infant-directed speech (IDS) collected at each different age (different-colored solid lines) and adult-directed speech (ADS) (dotted line). The x-axis indicates the frequency (spectral) band from which the AMs originate. The y-axis shows the PSI value. Error bars indicate the standard error of the mean. p < .001, and a signiﬁcant interaction between Condition and Spectral Band, F(12, 276) = 18.21, p < .001. However, Newman-Keuls post-hoc analysis revealed a reverse symmetry to the results obtained for the delta-theta AM band comparisons. For the majority of spectral fre- quency bands (ﬁrst, second, and fourth; 100–300 Hz; 300–700 Hz; 1,950–3,900 Hz), the IDS conditions showed lower PSI scores than ADS (p < .001 for all comparisons). However, PSI scores in the middle and highest spectral frequency bands (700–1,950 Hz; 3,900–7,250 Hz) did not differ between speaking conditions (p > .05 for all comparisons).

Control Analysis: Rate-Normalized Data

Figur 4 shows the mean number of syllables and
Syllables and Stressed Syllables per Second
stressed syllables produced per second for IDS and ADS, along with the mean proportion of
stressed syllables as a function of the total number of syllables produced. We used repeated
measure ANOVAs to compare speaking conditions in each case. For the number of syllables
produced, the ANOVA showed a signiﬁcant main effect of speaking condition, F(3, 69) =
74.42, P < .0001). Tukey post-hoc analysis showed that ADS had a signiﬁcantly greater num- ber of syllables per utterance than the three IDS conditions ( p < .001), which did not differ signiﬁcantly from each other. For the number of stressed syllables produced, the ANOVA again showed a signiﬁcant main effect of speaking condition, F(3, 69) = 3.42, p < .05. Tukey post-hoc analysis revealed signiﬁcantly more stressed syllables per second in ADS compared to IDS at 7 months and 9 months ( p < .05), but not IDS at 11 months. Finally, the ANOVA for the proportion of stressed syllables produced in the different speaking conditions also showed a signiﬁcant effect of condition, F(3, 69) = 28.33, p < .00001. Here, post-hoc tests showed that ADS contained a signiﬁcantly lower proportion of stressed syllables than IDS at any age (p < .001 for all comparisons). Therefore, although ADS contained more syllables and more stressed syllables than IDS within a given period of time (i.e., a quantitative rate effect), there was a qualitative difference between the speaking styles. Infant-directed speech contained a OPEN MIND: Discoveries in Cognitive Science 85 l D o w n o a d e d f r o m h t t p : / / d i r e c t . m i t . / e d u o p m i / l a r t i c e - p d f / / / / / 1 2 7 8 1 8 6 8 2 8 2 o p m _ a _ 0 0 0 0 8 p d . i f b y g u e s t t o n 0 7 S e p e m b e r 2 0 2 3 Modulation Structure of Infant-Directed Speech Leong et al. Figure 4. Mean number of syllables per second, stressed syllables per second, and proportion of syllables that were stressed for the infant-directed speech (IDS) and adult-directed speech (ADS) data for each speaking condition (“07” = 7 month IDS, “09” = 9 month IDS, “11” = 11 month IDS, “Ad” = ADS). higher proportion of stressed to unstressed syllables. In IDS, nearly half (~48%) of all syllables were stressed, whereas in ADS, only around one-third (~36%) of syllables were stressed. Modulation Spectrum The modulation spectra for the rate-normalized control data are shown in Figure 5 (panel a). Comparison with Figure 2 suggests that rate-normalization has not changed the pattern of IDS/ADS difference. A 3 × 4 ANOVA (Modulation Rate x Condition) showed the predicted interaction between Rate and Condition, F(6, 138) = 2.16, p < .05, one-tailed. Post-hoc anal- ysis (Fisher LSD) showed that IDS at 9 months contained signiﬁcantly more modulation energy in the delta band than in ADS (p < .05). For the theta band, ADS contained signiﬁcantly more energy than IDS at 7 and 9 months (p < .05 for both), but not at 11 months (p = .077). Finally, in the beta/low-gamma band, ADS contained signiﬁcantly more energy than IDS at 7 months (p < .05). Therefore, the patterns observed with natural speech were broadly conserved after the rate-normalization procedure. The PSI values obtained for the rate-normalized data are Phase synchronization (PSI) also shown in Figure 5 (panel b). Two 4 x 5 (Speaking Condition x Spectral Band) ANOVAs were again performed, again taking either delta-theta band PSIs or theta-beta/low-gamma band PSIs as the dependent variable. For the delta-theta band ANOVA, there were signiﬁcant main effects of Condition, F(3, 69) = 5.82, p < .01, and Spectral Band, F(4, 92) = 41.41, p < .0001, and a signiﬁcant interaction, F(12, 276) = 9.88, p = .0001. Tukey post-hoc analysis indicated that ADS had signiﬁcantly lower PSI scores (p < .001) than all three IDS conditions for the two lowest spectral frequency bands (100–300 Hz; 300–700 Hz). By contrast, for the middle spectral frequency band (700–1,950 Hz), PSI scores for ADS were signiﬁcantly higher than for IDS, but at 7 months only (p < .01). OPEN MIND: Discoveries in Cognitive Science 86 l D o w n o a d e d f r o m h t t p : / / d i r e c t . m i t . / e d u o p m i / l a r t i c e - p d f / / / / / 1 2 7 8 1 8 6 8 2 8 2 o p m _ a _ 0 0 0 0 8 p d . i f b y g u e s t t o n 0 7 S e p e m b e r 2 0 2 3 Modulation Structure of Infant-Directed Speech Leong et al. l D o w n o a d e d f r o m h t t p : / / d i r e c t . m i t . / e d u o p m i / l a r t i c e - p d f / / / / / 1 2 7 8 1 8 6 8 2 8 2 o p m _ a _ 0 0 0 0 8 p d . i f b y g u e s t t o n 0 7 S e p e m b e r 2 0 2 3 Figure 5. Panel (a). Mean modulation spectrum for rate-normalized infant-directed speech (IDS) (“07”, “09,” and “11” months) and adult-directed speech (ADS) (“Ad”) conditions, computed for each of ﬁve spectral frequency bands (100–300 Hz; 300–700 Hz; 700–1,750 Hz; 1,750–3,900 Hz; 3,900–7,250 Hz) and then averaged across bands and speakers. The x-axis shows the modula- tion rate, and the y-axis the power in dB (normalized with respect to the mean power of each frequency band in each sample). Vertical lines indicate the boundaries used to delineate the area under the curve for Spectral-Amplitude Modulation Phase Hierarchy (S-AMPH) delta-, theta- and beta/low-gamma-rate amplitude modulation (AM) bands. Panel (b). Phase Synchronization Index (PSI) values computed for the rate-normalized data, for delta-theta AM bands (left) and the theta- beta/low-gamma AM bands (right), for IDS collected at each different age (different-colored solid lines) and ADS (dotted line). The x-axis indicates the frequency (spectral) band from which the AMs originate. The y-axis shows the PSI value. Error bars indicate the standard error of the mean. For the theta-beta/low-gamma AM band ANOVA, there were again signiﬁcant main effects of Condition, F(3, 69) = 27.76, p < .00001, and Spectral Band, F(4, 92) = 96.69, p < .0001, and a signiﬁcant interaction, F(12, 276) = 15.30, p < .0001. Tukey post-hoc anal- ysis revealed that ADS scores were signiﬁcantly higher (p < .01) than IDS scores at all ages in the ﬁrst, second, and fourth spectral bands (100–300 Hz; 300–700 Hz; 1,950-3,900 Hz), but OPEN MIND: Discoveries in Cognitive Science 87 Modulation Structure of Infant-Directed Speech Leong et al. did not differ for the third and ﬁfth spectral bands (700–1,950 Hz; 3,900-7,250 Hz).Therefore, the results of the PSI analysis with rate-normalized data were again consistent with the PSI analysis conducted with natural speech. DISCUSSION The temporal modulation structure of IDS differs signiﬁcantly from that of ADS. First, there is signiﬁcantly greater modulation energy in the delta band in IDS relative to ADS, while ADS shows greater energy in the theta band compared to IDS. This difference is not simply a consequence of IDS typically being spoken more slowly than ADS, as demonstrated by the rate-normalized control analysis. The higher delta power in IDS was accompanied by a higher proportion of syllables being stressed in IDS as compared to ADS, providing a more rhythmic input. Second, IDS showed signiﬁcantly greater phase synchronization between the slower delta- and theta-rate AM bands compared to ADS. This ﬁnding was also mirrored in the con- trol analysis with rate-normalized data. Accordingly, there are clear differences in the pattern of rhythmic synchronization between IDS and ADS. Greater phase synchronization between delta- and theta-rate AM bands accompanies greater rhythmic regularity in IDS: syllables are stressed more regularly. These ﬁndings have important implications for the neural basis of language acquisition, at least for English. The temporal rate bands at these different timescales can be assumed to entrain neuronal oscillatory activity (Giraud & Poeppel, 2012). For adult speech, oscillations in the delta (1–3 Hz), theta (4–8 Hz), and beta/low-gamma bands (15–30 Hz / >30 Hz) bzw-
tively have been shown to be critical for encoding (frequency ranges from Poeppel, 2014).
One proposal is that oscillatory entrainment to amplitude modulations in these bands helps to
parse the speech signal into linguistically relevant units (delta—syllable stress patterns, theta—
syllables, beta—onset-rime units, low gamma—phonetic information). Our data suggest that
IDS is acoustically structured to facilitate neural entrainment to delta band (prosodic) informa-
tion by the infant brain. In der Tat, a large infant behavioral literature attests to the importance
of stressed syllables in early word segmentation (z.B., Cutler & Norris, 1988; Echols, 1996).
Weiter, at least two studies of infant entrainment to nonspeech AMs have revealed signiﬁcant
neuronal entrainment in this frequency range for German-learning infants, including new-
borns (Telkemeyer et al., 2009; Telkemeyer et al., 2011). The stronger phase synchronization
between delta- and theta-rate AM bands that characterizes IDS would further facilitate the ex-
traction of rhythmic patterning, Zum Beispiel, in distinguishing trochaic versus iambic prosodic
Struktur (Leong, Stein, et al., 2014). The infant electrophysiological literature shows that in-
fants are encoding the difference between trochees and iambs by 4 Monate alt (Weber et al.,
2004). These differences in phase synchronization strength between slower (IDS) versus faster
(ADS) timescales could also be related to recent demonstrations that phonetic contrasts in
IDS are less clear than in ADS (Martin et al., 2015; McMurray, Kovack-Lesh, Goodwin, &
McEchron, 2013).

In der Tat, phase synchronization at faster modulation timescales was greater in ADS, Und
this effect was also preserved in the rate-normalized data. Perceptually, this would increase the
rhythmic regularity of the acoustic relationship between syllables and phonemes, which could
potentially reﬂect the acquisition of literacy. A more regular temporal patterning of phonemes
within syllables may reﬂect the explicit awareness of phonemes in syllables that is a cognitive
consequence of learning to read (see Ziegler & Goswami, 2005, for data across languages).
Entsprechend, ADS may show stronger acoustic patterning at faster temporal rates because most
ADS speakers are literate. Experimental investigation of the temporal modulation structure of

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Modulation Structure of Infant-Directed Speech Leong et al.

ADS as produced by literate versus illiterate populations offers one method for exploring this
possibility further (Araújo, Flanagan, Castro-Caldas, & Goswami, 2016).

ACKNOWLEDGMENTS

We thank Maria Christou-Ergos for preparation of data for analysis. This work was supported by
funding from the Australian Research Council (DP110105123) to DB and UG. Victoria Leong
is now in the Division of Psychology, Nanyang Technological University, Singapur.

BEITRÄGE DES AUTORS

VL, DB, and UG conceived and designed the study, MK and DB collected the data, VL analyzed
the data, VL, MK, DB, and UG wrote the article.

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8
2
8
2
Ö
P
M
_
A
_
0
0
0
0
8
P
D