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Journal of Child Language
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Input and uptake at 7 months predicts toddler
vocabulary: the role of child-directed speech and
infant processing skills in language development
ROCHELLE S. NEWMAN, MEREDITH L. ROWE and NAN BERNSTEIN RATNER
Journal of Child Language / FirstView Article / August 2015, pp 1 - 16
DOI: 10.1017/S0305000915000446, Published online: 24 August 2015
Link to this article: http://journals.cambridge.org/abstract_S0305000915000446
How to cite this article:
ROCHELLE S. NEWMAN, MEREDITH L. ROWE and NAN BERNSTEIN RATNER
Input and uptake at 7 months predicts toddler vocabulary: the role of child-directed
speech and infant processing skills in language development. Journal of Child
Language, Available on CJO 2015 doi:10.1017/S0305000915000446
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BRIEF RESEARCH REPORT
Input and uptake at months predicts toddler
vocabulary: the role of child-directed speech and infant
processing skills in language development
ROCHELLE S. NEWMAN*
University of Maryland, USA
MEREDITH L. ROWE
Harvard University, USA
AND
NAN BERNSTEIN RATNER
University of Maryland, USA
(Received October –Revised June –Accepted August )
ABSTRACT
Both the input directed to the child, and the child’s ability to process
that input, are likely to impact the child’s language acquisition. We
explore how these factors inter-relate by tracking the relationships
among: (a) lexical properties of maternal child-directed speech to
prelinguistic (-month-old) infants (N = ); (b) these infants’
abilities to segment lexical targets from conversational child-directed
utterances in an experimental paradigm; and (c) the children’s
vocabulary outcomes at age ;. Both repetitiveness in maternal input
and the child’s speech segmentation skills at age ;predicted
language outcomes at ;; moreover, while these factors were
somewhat inter-related, they each had independent effects on toddler
vocabulary skill, and there was no interaction between the two.
INTRODUCTION
A great deal of research (summarized briefly below) has explored how the
amount/nature of child-directed speech (CDS) might influence children’s
[*] Address for correspondence: University of Maryland –Hearing and Speech, Lefrak
Hall, College Park Maryland , United States. e-mail: rnewman@umd.edu
J. Child Lang., Page of . © Cambridge University Press
doi:./S
language outcomes. Other work has looked at the abilities that young infants
bring to the table, such as the extensively studied ability to bootstrap
language characteristics by locating individual words in fluent speech (also
known as segmentation). These skills may themselves be impacted by the
input to the child. But with few exceptions (e.g. Hurtado, Marchman &
Fernald, ; Weisleder & Fernald, ), investigations of infant skills
and of the input children receive have been studied separately, without
asking how their respective contributions might interact to influence
children’s vocabulary acquisition.
In this paper, we track the relationships among the lexical properties of
CDS to a large sample (N = ) of prelinguistic (-month-old) infants,
infant segmentation skill (or the ability to separate and identify those
lexical items), and the children’s vocabulary outcomes at age ;.Wefirst
discuss what is currently known about the impacts of CDS on children’s
language development. We then review what is known about infant speech
processing skills, particularly segmentation, and its potential role in
predicting children’s later language abilities. Finally, we discuss a small
body of recent research that reports interactions between children’s
linguistic experience and speech processing abilities before presenting the
current investigation and its findings.
CDS and children’s language learning
Adults speak differently to language-learning children than to more mature
listeners (see Bernstein Ratner, ; Soderstrom, , for summaries);
they also ‘fine-tune’these speech adjustments to the child’s perceived
comprehension abilities (see Snow, , for discussion). There are
documented changes in infants’preferences for input (e.g. Hayashi,
Tamekawa & Kiritani, ; McRoberts, McDonough & Lakusta, ),
suggesting possible synergies between infant preferences, adult language
modification, and benefits to child language learning. However, the
long-term effect of variability in CDS on later communication outcomes is
less evident.
Studies of the effect of CDS have explored a number of properties,
ranging from phonetic properties (such as vowel space; Liu, Kuhl & Tsao,
), through grammatical components (e.g. Ambridge, Rowland,
Theakston & Kidd, ), and pragmatic features (e.g. Hirsh-Pasek et al.,
; Tamis-LeMonda, Bornstein & Baumwell, ; Tomasello &
Farrar, ). In the present paper, we focus particularly on characteristics
at the lexical level, as that level is one where children’s own processing
skills can be easily explored at the same age as parental input. Research
suggests that input registers characterized by more verbosity and diversity
appear to facilitate vocabulary development in toddlers and preschoolers.
NEWMAN ET AL.
For example, Hoffand Naigles () found that quantity of speech and
lexical diversity predicted lexical achievement in two-year-old children
(N = ). Diversity of CDS vocabulary has been linked to outcomes at age
two and beyond in middle-class families (Bornstein, Haynes & Painter,
; Hart & Risley, ;Hoff-Ginsberg, ; Huttenlocher, Haight,
Bryk, Seltzer & Lyons, ) and lower SES families (Pan, Rowe, Singer
& Snow, ; Shimpi, Fedewa & Hans, ). Increases in the number
of child-directed words (tokens in the input) as well as types (unique
words) and rare / less common words correlate with higher levels of child
vocabulary (Rowe, ; Weizman & Snow, ). However, few studies
have investigated CDS to infants under months, or specific aspects of
input that may be beneficial at this early age.
Although there is a general sense that more language input and thus more
words leads to better language outcomes, different features of CDS may play
a larger or smaller role at different points in development. Furrow, Nelson,
and Benedict () argued that “what leads to a change in the system at one
point in development may be completely ineffective at another point”, and
Bohannon and Leubecker () cautioned that CDS consists of
“reciprocal, non-linear relations”. While input quantity is clearly
important, other specific features of input are helpful over and above
quantity, and the more we understand about these helpful features of
input the more we can learn about the mechanisms involved in language
learning (e.g. Rowe, ,). Conceivably, while ‘more words’in the
input may generally be important, early in the first year of life repetition
of words may be particularly useful, whereas lexical diversity is
linguistically enriching later on. Indeed, McRoberts et al. () reported
that -month-old infants show preference for repeated, as opposed to
novel, utterances. It also could be important how often parents provide
their children with input that does not require segmentation to identify
the words (e.g. -word utterances); Brent and Siskind () reported that
exposure to a word in one-word utterances predicted the likelihood that
the child would later use that word productively.
The role of processing in language learning
Most CDS studies have not tracked children’s concurrent speech processing
skills. A notable exception is Hurtado et al. (), who tracked
twenty-seven children between the ages of ;and ;; those whose
mothers provided richer input at ;(as estimated by automated counts of
mothers’CDS by the LENA software system) had higher vocabulary
scores and faster word recognition at ;. The authors concluded that
enriched input influences lexical processing efficiency and that such
improvements can work synergistically to advantage children. The team
CDS AND INFANT SEGMENTATION
extended findings to twenty-nine Spanish-learning infants studied between
ages ;and ;(Weisleder & Fernald, ). Richer input at ;(again,
as estimated by CDS words recorded by LENA) predicted children’s
vocabulary at age ;, and the speed with which the toddlers oriented to
images when presented with a word in the laboratory. Thus, maternal
input spurred vocabulary learning, and also led to improved capacity to
attend to and process incoming speech information, which in turn was
independently associated with better vocabulary outcomes.
Most CDS consists of multiword utterances (e.g. Aslin, Woodward,
LaMendola & Bever, ) without obvious signals demarcating word
boundaries. Infants must somehow subdivide utterances into individual
units (word segmentation). Early segmentation investigations familiarized
infants with isolated monosyllabic target words (Jusczyk & Aslin, ).
Infants were then tested on their ability to recognize these same words in
fluent speech stimuli. At ;· (but not ;, at least for English), infants
demonstrated ability to segment words from fluent speech (see also
Jusczyk, Houston & Newsome, ). Segmentation shows a gradual
developmental timecourse, and infants appear to use a variety of cues to
segment (Jusczyk, , and subsequent work). Thus, there is individual
variability; similar-aged children may differ in abilities or strategies. For
example, of twenty-four infants in the first experiment of the Jusczyk
et al. () study, only eighteen showed segmentation skill –in short,
children regularly show non-uniform performance patterns.
Does failure to perform well in a laboratory-based segmentation or similar
speech perception task have implications for later language development?
Failure should presumably delay vocabulary acquisition, and a recent
meta-analysis documents that infant speech perception performance
predicts later language skill equally as well as non-linguistic measures,
such as habituation/dishabituation and/or rapid auditory processing tasks
(Cristia, Seidl, Junge, Soderstrom & Hagoort, ). Segmentation
abilities are delayed in children with cognitive/linguistic deficits (Nazzi,
Paterson & Karmiloff-Smith, ), in line with the notion that
segmentation could be a necessary precursor for typical language
development. A retrospective analysis found that typically developing
infants aged ;–;who fail laboratory segmentation tasks have
significantly poorer age ;language outcomes than do successful infants
(Newman, Bernstein Ratner, Jusczyk, Jusczyk & Dow, ). Further, at
age ;–;, those children who had failed laboratory segmentation tasks as
infants demonstrated lower syntactic and semantic skills, but did not differ
in general intellectual abilities, suggesting that infant segmentation may
specifically predict language development. Singh, Reznick, and Xuehua
() recently extended this finding. They prospectively correlated
children’s laboratory performance (on both simple and complex
NEWMAN ET AL.
segmentation tasks) at ;· and their vocabulary outcomes at ;.
Similarly, Junge and colleagues (e.g. Junge, Kooijman, Hagoort & Cutler,
) reported that infants with more advanced ERP patterns at ;had
larger language quotients at ;and larger receptive vocabularies at ;.
Thus, infants’failure on laboratory segmentation tasks may signal a
language-processing developmental lag, rather than transient inattention
during testing (see Cristia et al.,, for more extensive discussion).
The current study
Children’s ability to segment CDS may predict later language outcomes.
Similarly, the quantity of CDS available to be segmented (Bornstein et al.,
; Hart & Risley, ; Huttenlocher et al.,) and lexical
properties such as vocabulary diversity (Hoff,; Pan et al.,;
Rowe, ) lead to differential outcomes in language development. Yet
no work to date has explored both lexical input and segmentation ability
within the same cohort, as Cristia et al. () observe. We evaluate how
these factors relate to one another and jointly predict later language skills,
using a much larger cohort of children than in prior studies.
Specifically, our goals were:
. To replicate findings that segmentation ability at ;positively predicts
vocabulary at ;;
. To examine whether lexical aspects of maternal input at ;predict child
vocabulary at ;;
. To determine whether segmentation ability and input simultaneously
predict child vocabulary at age ;and whether there is interaction
between the two predictors.
METHODS
Participants
One hundred and twenty-one mother–child ( male) dyads participated in a
longitudinal project with multiple visits across a two-year span (initial goal
had been completed participants). Our sampling strategy and
summary of attrition is described in Table . One hundred and
seventy-three families were initially tested, but twenty-eight were excluded
prior to one year of age because of family move or request for removal
(n = ); genetic disorder or health issues (n = ); or only the father being
free to participate (n = ). Data from an additional ten participants were
removed either because the child was not learning English as the majority
language at some point during the study (some children began hearing
English the majority of the time but their language exposure changed over
the course of the study) or because the mother was not a native speaker of
CDS AND INFANT SEGMENTATION
English. Finally, an additional fourteen children were later excluded because
they failed to attend the final visit (n = ) or had been identified with a
language disorder during their second year (n = ), leaving participants.
Mothers averaged ·years of education (range: HS diploma to PhD.);
fathers had ·years. Ethnicity was % Caucasian, % African-
American, % Hispanic, ·% Asian, and ·% Native-American/Pacific-
Islander. Age at first visit ranged from ;· to ;·(average ·
months). Age at the two-year visit ranged from ;·to ;·(average
·months). Numbers of participants vary slightly across analyses as
noted, due to sporadic incomplete data (e.g. audios of maternal input were
distorted/uncodable for participants, etc.).
Dyads participated in a range of tasks at multiple ages designed to address
a variety of theoretical questions; the current paper explores those measures
specifically focused on segmentation, maternal input, and vocabulary
outcomes.
Segmentation task, age ;.
The task was modeled after Jusczyk and Aslin (). Infants sat on their
caregiver’s lap in a three-sided test booth. An experimenter hidden behind
the booth pressed a button on a response box to indicate direction of the
child’s looking behavior. At trial start, a center light in the front panel
flashed. When the child responded, it was extinguished and a side panel
light began to flash. Once the child looked towards that light, a sound file
TABL E .Summary of participants
Participant group
Number
of dyads Reason for exclusion
Initially tested at ·months
Participants who were still
enrolled at one year of age
genetic disorder or health reasons (n = ); only
father could attend (n = ); moved out of area or
did not return after first visit (n = ); mother
non-native speaker or child not majority
English (n = )
Dyads who returned for final
visit
Could not schedule final visit (n = ); identified
with a language disorder prior to ;(n = );
language percentage at end of study (n = )
Included in final analyses Incomplete MCDI data (n = ); MCDI of less
than words (n = )
Included in maternal speech
analyses
Missing audio file of maternal speech (n = )
Included in segmentation
analyses
Fussed out of laboratory task (n = ); refused to
look towards the flashing lights (n = );
equipment failure (n = )
Included in combined analyses (combination of exclusions above)
NEWMAN ET AL.
played from a hidden loudspeaker, continuing until the child looked away for
two consecutive seconds, at which point the next trial began. Total amount
of looking time to the flashing light was calculated as a measure of listening
time; any time the infant spent looking away (s or less) was excluded.
There were familiarization and test phases. During familiarization,
children heard repetitions of two words (bike and feet)ondifferent trials,
until they accumulated a total of s of listening time to each word.
During test phases, children heard sixteen trials (blocks of trials). In
each trial, children heard a six-sentence passage focused on one of four
target words: bike, feet, cup, and goat (e.g. “The goat pranced across the
field. He saw a really big goat. He patted his goat on the back.”; we used
goat rather than dog, as Jusczyk and Aslin did, because dog engenders
extreme preferences in some infants, unlike other words in the set, a
concern for an individual-difference study; in addition, our location on a
dialectal border could affect family production of that vowel in particular).
Each block contained one trial for each passage, in random order. Average
listening time to passages containing the two novel words was compared to
trials containing familiarized words. Data were analyzed from all
participants who completed at least three of the four blocks without
fussing out ( of children). The experimenter and caregiver wore
Peltor Aviation headphones playing masking music to block hearing the
stimuli and biasing the child’s behavior or subsequent coding.
Input assessment, age ;.
After the segmentation task, dyads played with a standard set of toys,
including plush animals, baby doll with accessories, food-/eating-/
cooking-related items, and board books. Mothers were asked to play with
their children as they would normally at home. They were informed that
they were being video- and audio-recorded, and asked to wear an
Audio-Technica AT lavalier microphone connected to a Marantz
PMD solid-state digital recorder; mothers were told that while our
intent was to record the child, they should wear the microphone so that
their child would not play with it. Sessions lasted approximately
minutes. All recordings were transcribed via sonic CHAT mode using
TalkBank utilities (MacWhinney, ). Transcripts were analyzed using
CLAN for total amount of input (tokens), vocabulary diversity (types),
and repetitiveness of the input (type–token ratio, or TTR), and for the
percentage of utterances that were a single word in length.
Vocabulary assessment, age ;
Children returned at approximately two years of age. At this visit, parents
completed the MacArthur-Bates Communicative Development Inventory
CDS AND INFANT SEGMENTATION
(Fenson et al.,). Children’s vocabulary scores on the MCDI at age ;
varied widely. Three children had scores below words, suggesting
possible clinically relevant delay and were excluded from further analyses;
MCDI scores were unavailable for one additional child, resulting in a final
sample of n = . Mean MCDI score was ·(SD = ·, range = –
), comparable to original norming study scores (Fenson, Dale, Reznick,
Bates, Thal & Pethick, ; mean = words, SD = ). MCDI scores
were normally distributed in this sample.
RESULTS
We first sought to replicate our previous retrospective finding (Newman
et al.,) that infants’ability to segment fluent speech predicted later
vocabulary skill. Of the participants with usable MCDI scores, did
not complete the laboratory task (fussed out (n = ), refused to look
towards the flashing lights (n = ), or equipment failure (n = )). Thus,
participants were available for analysis; looking time was normally
distributed. The earlier study split children into two groups based on
vocabulary, looking only at the top and bottom %; however, we had a
smaller sample, and thus included all children, splitting into two
equivalent groups. We compared children with higher (MCDI > ) and
lower (MCDI < ) vocabulary scores. Children in the upper-MCDI
group showed a greater novelty preference on the segmentation task than
children in the lower-MCDI group (t()=·,p<.), thus replicating
our previous finding of a relationship between segmentation and later
outcomes. (Correlations across MCDI scores showed a similar relationship:
r()=·,p<.) However, the direction of this relationship was
different from the previous study: we found that novelty, not familiarity,
preferences led to larger vocabulary scores, a point we return to in the
‘Discussion’.
We next asked whether maternal input at child age ;· predicts MCDI
scores at ;. Maternal input was unavailable for two dyads due to poor
recordings; thus, this analysis included / families with usable
MCDI scores (we included children who did not complete the
segmentation task successfully). CLAN was used to compute maternal
tokens, types, and TTR in -month-directed CDS, and the percentage of
utterances that were a single word in length. Maternal tokens ranged from
to (M = ·). Maternal types ranged from to (M =
·). Maternal TTR ranged from · to · (M = ·). Lower TTR
indicates more repetition. Mothers varied in the percentage of one-word
utterances from · to · (M = .). All four of the input measures
were normally distributed and did not require transformation. Children’s
two-year MCDI scores were significantly positively correlated with
NEWMAN ET AL.
mothers’tokens (r=·) and types (r=·), and significantly negatively
correlated with TTR (r=–·). That is, children’s vocabulary scores were
higher if their mother produced more words, and more different words,
but also if their mothers used more repetition. Children’s two-year MCDI
scores did not correlate significantly with the percentage of one-word
utterances that mothers used (r=–·). TTR had the strongest
association with the MCDI scores, thus we opted to use TTR as the input
measure for further analysis. Unsurprisingly, maternal tokens, types, and
TTR are all significantly inter-correlated. Interestingly, controlling for
types, the relation between TTR and MCDI is still significant (r=–·,
p<.), but when controlling for tokens, it is not (r=–·,p=·).
Are infants’abilities to segment speech at ;· and maternal
repetitiveness at that same age related? Segmentation ability might already,
even at this early age, be affected by the input children receive. The two
measures marginally correlate (r()=·,p<.); thus, in this sample,
there is a tendency for infants showing a novelty preference on
segmentation tasks to hear more repetition from mothers. We return to
this finding when we model the relationship among these variables and
child language outcomes.
We last asked whether child segmentation ability and maternal input, when
considered simultaneously, explain unique variation in child vocabulary at age
;. We conducted multiple regression analyses using infant novelty
preference and maternal input (TTR) as predictors of children’sMCDI
scores (all as continuous measures) at age ;(see Table ). Although it is
unclear whether segmentation results from a study using the head-turn
preference procedure task should be measured continuously (looking time)
or categorically (looking longer to the appropriate item vs. not doing so),
this choice does not change the pattern of results. Data include the
ninety-four participants having segmentation, TTR, and MCDI data
available. Model (Table ) shows the independent significant effect of
child segmentation ability at ;· on MCDI scores at age two. In this
model, infants’segmentation ability explains ·% of variation in toddler
vocabulary skills. Model presents the independent significant effect of
maternal repetitiveness at ;· on child MCDI scores at age two. In this
model, maternal input at ;· explains ·% of the variation in
two-year-old child vocabulary. Model includes both infant segmentation
ability and maternal input as simultaneous predictors. In this model, both
predictors remain significant and the amount of variation explained
increases to nearly %. Thus, when considered together, both child
segmentation ability and parent repetitiveness at child age ;· are
significantly related to children’s vocabulary skill at ;, as measured on the
MCDI. A change in R-square statistic was calculated to determine whether
Model was a significantly better fitting model than Models or , despite
CDS AND INFANT SEGMENTATION
the inclusion of an additional predictor. The comparisons resulted in Partial F
statistics of · (Model vs. )and· (Model vs. ), which are both
greater than the corresponding alpha = · critical F-value of ·. Thus,
Model , which contains the effects of both infant segmenting and maternal
input, is a significantly better fitting model than Model or .InModel,
we added the interaction term between segmentation ability and input to
determine whether the effect of input differed based on segmentation
ability. The interaction was non-significant. As a final step, not shown in
the table, we considered potentially important control variables. Neither
parent education (fairly homogenous in this sample), nor child gender
related to MCDI scores at age ;, with TTR and segmentation ability in
the model, and thus were not retained in the analysis. We also examined
the joint impact of the percentage of one-word utterances and segmentation
ability, and their interaction, on vocabulary outcomes, in case the
percentage of one-word utterances was particularly important in children
whose segmentation skills were weak, but found no relationships. Thus, our
final model is Model , suggesting that both infant skills (segmenting) and
repetitiveness in the input (TTR) at ;· contribute to children’slater
productive vocabulary size. Residuals from this model were examined and
did not violate any of the regression assumptions.
DISCUSSION
Most children acquire their native language successfully and rapidly over a
very short time frame in the first years of life. But some children do not
TABL E .Regression models predicting child vocabulary production at age two
(MCDI) based on infant segmenting ability and maternal input at age ·
months (n = )
MCDI scores at age two
β-coefficient (standard error)
Predictors Model Model Model Model
Intercept ·** ·** ·** ·**
(·)(·)(·)(·)
Infant segmenting ·*·*−·
(·)(·)(·)
Maternal input −·** −·*−·*
(·)(·)(·)
Segmenting x input interaction ·
(·)
R-squared stat (%) ····
NOTES:*p<.;**p<·.
NEWMAN ET AL.
acquire language as well as others, and we are as yet unable to predict which
children will be more or less successful language learners. We examined the
potential contributing roles of two factors at age ;·: (i) infants’ability to
break up fluent speech into individual words (segmentation); and (ii) the
input that children hear from their mothers. Each has been argued to be a
critical underpinning for language acquisition; however, most work on the
role of input investigates CDS to children older than ;·. Both
maternal input (repetitiveness) and speech segmentation skills at ;·
predicted child language outcomes at ;; moreover, while these factors
were somewhat related to one another, they each had independent effects
on toddler vocabulary skill.
These results support prior retrospective and prospective work (e.g.
Newman et al.,; Junge et al.,; Singh et al.,), suggesting
that children’s laboratory performance may reveal individual speech
processing skills. Moreover, this ability contributed significantly to
vocabulary outcome scores even once maternal input was factored in,
suggesting that segmentation skills are not isomorphic with input patterns,
though they may share a partially mediated relationship. Rather, this
segmentation task may measure children’s processing abilities, independent
of their environmental exposure. Clearly, future work should explore this
more fully by examining parental input prior to ;., our earliest
datapoint. Because at this age both segmentation ability and maternal
input appeared to contribute independently to the child’s language profile
at age two, the directionality of this association is unclear. Processing skill
and input style may be independent, or interact in ways currently
unknown, such that maternal input style may have given our young infant
participants benefits in facing segmentation task challenges, or that infants
with better segmentation skills could better capitalize on a particular
maternal style of input. McRoberts et al. () suggest that “attention to
repeated utterances precedes word segmentation and statistical cues in
continuous speech”. This suggests that repetition in infant-directed speech
actually primes the child’s ability to segment. In McRoberts et al.,
six-month-old children (younger than our youngest subjects) particularly
showed preference for a more repetitive infant-directed signal. Further,
our analyses found a marginal correlation between CDS repetitiveness and
child segmentation ability. Additional longitudinal research, starting at
younger ages, may enlighten the directionality of the relationship between
infant segmentation ability and experience with particular profiles of CDS
in their environment.
In the current study, infants who showed novelty preferences in the
segmentation task showed larger later vocabularies, rather than infants who
showed familiarity preferences, as suggested in our prior work. The
interpretation of novelty vs. familiarity preferences in infants is a matter of
CDS AND INFANT SEGMENTATION
long-standing concern (Burnham & Dodd, ; Houston-Price & Nakai,
; Slater, ). Burnham and Dodd note that “From one point of
view, it can be argued that the valence of the preference is unimportant,
for as long as there is a preference, then discrimination is demonstrated”
(p. ). Cristia et al. () briefly discuss the problem of understanding
which type of preference is predictive of later outcomes, given various ages
and tasks. Here, we were not testing discrimination per se, but evaluating
how individual differences in the ability to make a discrimination (between
familiarized and unfamiliarized words) predicted later abilities. Many
factors influence whether a particular infant shows novelty vs. familiarity
preferences (e.g. stimulus complexity, familiarization time). In general,
children seem to show novelty preferences when they are more ‘bored’
with the stimulus, because it is inherently less interesting / simpler,
because it has been presented more times, or because they have completed
processing. This suggests that more cognitively advanced infants should be
more likely to show novelty preferences, since they will process more
quickly, in line with the current results (where infants showing a stronger
novelty preference were more advanced in vocabulary acquisition rates).
Nonetheless, the variation across studies is of concern, and may encourage
the use of other paradigms in future work, such as ERPs (as in Junge
et al.,), where such shifts over time or development are less likely to
occur. That said, there were also some important differences between this
study and prior work. In particular, all the children in the current
experiment participated in the same segmentation task –one that focused
on monosyllabic words spoken by the same talker. In contrast, the
Newman et al. () paper retrospectively examined a large set of
children who had participated in a variety of segmentation studies, and
collapsed data across these different studies. The studies themselves
included ones in which the talker varied between training and test, where
the words were multisyllabic, or where there was a limited set of acoustic
cues available. In other words, the current study used a simpler (likely
easier) segmentation task –this may help explain why novelty preference,
rather than familiarity preference, was seen here.
Cristia et al. () note that the infant’s linguistic environment cannot be
ignored in trying to link speech perception task performance and children’s
later linguistic skills. In the current study, both the input and the child’s
processing proclivities appear to work synergistically to provide benefitto
the language-learning process. This may explain, in part, why, for input to
aid in child language acquisition, it must be child-addressed, and not
merely overheard (Shneidman & Goldin-Meadow, ; Weisleder &
Fernald, ). Our findings also confirm that input addressed to quite
young infants, who show rudimentary comprehension in naturalistic
conversations, and only prelinguistic levels of verbal expression, does have
NEWMAN ET AL.
a measurable impact on the rate of language development over the first two
years of life. At these early stages, it is access to repeated instances of words
that appears to facilitate mapping of lexical targets.
There were no effects of either gender or parent education on children’s
outcomes once input and segmentation abilities were entered into the
equation. Lack of an SES effect may reflect limited diversity in our
sample; only eleven mothers had less than a college education, with only
one without some education post-high school. The fact that profiles of
interaction even within this rather privileged sample appeared to influence
children’s outcomes at age two is significant for its ramifications on the
quality of child care (particularly adult–infant ratio) in less advantaged
communities, for children under the age of one year. However, the lack of
an effect of gender may be more surprising.
We also found no effect of the percentage of one-word utterances that
parents used; mothers’use of single-word utterances might have been
expected to interact with children’s segmentation ability, in that children
with weaker segmentation skills might benefit from parents who provided
already segmented input. That did not appear to be the case, however.
These findings also seem to contradict those of Brent and Siskind (),
who found a relationship between mothers’use of words in isolation and
children’s vocabulary acquisition. However, Brent and Siskind examined the
relationship between individual words being produced in isolation, and the
likelihood of those particular words being learned by children; in contrast,
we calculated the proportion of maternal one-word utterances overall, and
related that to the size of children’s productive vocabulary, without
attempting to identify whether there was specific overlap among word sets.
Critically, we only explored vocabulary outcomes within typically
developing children; although we identified children whose vocabulary
scores satisfy a diagnosis of Specific Emergent Language Delay (a
precursor to specific language impairment, or SLI), our sample included
only three such children. This was not a sufficient number to explore
possible predictors for this group, and thus we excluded them from our
analysis. However, one direction for future work would be to explore
aspects of both nature and nurture that could predict those children most
at risk for later language difficulties.
In the end, our data provide further evidence for the role of the child and
the role of environmental (i.e. input) effects in early vocabulary
development. Both are critically important to the eventual outcome.
Moreover, our finding of specific lexical input profiles linked to higher
levels of vocabulary knowledge is of extreme practical importance, since
vocabulary both measures and enables scholastic achievement (Snow,
Burns & Griffin, ). It appears that the REPETITIVENESS of the
vocabulary input with -month-old children is a key factor. Finding an
CDS AND INFANT SEGMENTATION
association between input profiles at an early age and later language skill
enables us to guide parents, caretakers, and childcare policy to maximize
children’s language and educational potential.
ACKNOWLEDGEMENTS
This work was supported by NSF grant BCS to the University of
Maryland. The authors thank Lisa Tuit, Sean Hendricks, and Amelie Bail
for conducting much of the testing of the assessments at age ;, and
Devon Brunson, who performed most of the scheduling. We particularly
thank Giovanna Morini for helpful oversight and commentary, and Kelly
Hartman, Kerry McColgan, Julia Sampson, Jenna Poland, Christina
Royster, and Anna Synnesvedt for coding oversight. The authors also
thank the following students for assistance in recruiting and scheduling
families or transcribing test sessions: Katrina Ablorh, Candace Ali, Saher
Ali, Alison Arnold, Megan Askew, Catherine Bender, Taryn Bipat,
Michelle Cass, Danielle Chazen, Alyssa Cook, Jennifer Coon, Sara Davis,
Justine Dombroski, Sara Dougherty, Cathy Eaton, Sara Edelberg, Daniel
Eisenberg, Meaghan Ervin, Lauren Evans, Andrea Farina, Josefina
Fernandez, Lauren Fischer, Andrea Fisher, Arielle Gandee, Richard
Garcia, Whitney Goodrich-Smith, Eliana Groskin, Natalie Hein, Laura
Horowitz, Tim Howell, Megan Janssen Crenshaw, Mina Javid, Amanda
Jensen, Jamie Karen, Caroline Kettl, Michelle Keenan, Esther Kim,
Stephanie Lee, Perri Lieberman, Rachel Lieberman, Danielle Lindenger,
Rachel Lipinski, Katie Lippitt, Debbie Martinez, Jenn McCabe, Eileen
McLaughlin, Kelly McPherson, Debra Mirazhi, Vidda Moussavi, Molly
Nasuta, Ashley Nimmo, Courtenay O’Connor, Sabrina Panza, Elise
Perkins, Amanda Pasquarella, Lauren Polovoy, Rachel Ports, Rachel
Rhodes, Allie Rodriguez, Maria Rodriguez, Judith Segal, Katie
Shniderman, Veronica Son, Mara Steinberg, Sarah Steele, Justine Taweel,
Allison Temple, Dena Tran, Hillary Tyler, Eugene Vassilas, Susan
Veppumthara, Krista Voelmle, Chelsea Vogel, Amanda Wildman, Cavena
Williams, Kimmie Wilson, Catherine Wu, Donna Zack-Williams and
Michelle Zobel.
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