Can infants map meaning to newly segmented words? Statistical segmentation and word learning

The present experiments investigated how the process of statistically segmenting words from fluent speech is linked to the process of mapping meanings to words. Seventeen-month-old infants first participated in a statistical word segmentation task, which was immediately followed by an object-label-learning task. Infants presented with labels that were words in the fluent speech used in the segmentation task were able to learn the object labels. However, infants presented with labels consisting of novel syllable sequences (nonwords; Experiment 1) or familiar sequences with low internal probabilities (part-words; Experiment 2) did not learn the labels. Thus, prior segmentation opportunities, but not mere frequency of exposure, facilitated infants' learning of object labels. This work provides the first demonstration that exposure to word forms in a statistical word segmentation task facilitates subsequent word learning.     

A computational model of word segmentation from continuous speech using transitional probabilities of atomic acoustic events

Word segmentation from continuous speech is a difficult task that is faced by human infants when they start to learn their native language. Several studies indicate that infants might use several different cues to solve this problem, including intonation, linguistic stress, and transitional probabilities between subsequent speech sounds. In this work, a computational model for word segmentation and learning of primitive lexical items from continuous speech is presented. The model does not utilize any a priori linguistic or phonemic knowledge such as phones, phonemes or articulatory gestures, but computes transitional probabilities between atomic acoustic events in order to detect recurring patterns in speech. Experiments with the model show that word segmentation is possible without any knowledge of linguistically relevant structures, and that the learned ungrounded word models show a relatively high selectivity towards specific words or frequently co-occurring combinations of short words.     

All words are not created equal: expectations about word length guide infant statistical learning

Infants have been described as ‘statistical learners’ capable of extracting structure (such as words) from patterned input (such as language). Here, we investigated whether prior knowledge influences how infants track transitional probabilities in word segmentation tasks. Are infants biased by prior experience when engaging in sequential statistical learning? In a laboratory simulation of learning across time, we exposed 9- and 10-month-old infants to a list of either disyllabic or trisyllabic nonsense words, followed by a pause-free speech stream composed of a different set of disyllabic or trisyllabic nonsense words. Listening times revealed successful segmentation of words from fluent speech only when words were uniformly disyllabic or trisyllabic throughout both phases of the experiment. Hearing trisyllabic words during the pre-exposure phase derailed infants’ abilities to segment speech into disyllabic words, and vice versa. We conclude that prior knowledge about word length equips infants with perceptual expectations that facilitate efficient processing of subsequent language input.     

Computation of Conditional Probability Statistics by 8-Month-Old Infants

A recent report demonstrated that 8-month-olds can segment a continuous stream of speech syllables, containing no acoustic or prosodic cues to word boundaries, into wordlike units after only 2 min of listening experience (Saffran, Aslin, & Newport, 1996). Thus, a powerful learning mechanism capable of extracting statistical information from fluent speech is available early in development. The present study extends these results by documenting the particular type of statistical computation–transitional (conditional) probability–used by infants to solve this word-segmentation task. An artificial language corpus, consisting of a continuous stream of trisyllabic nonsense words, was presented to 8-month-olds for 3 min. A postfamiliarization test compared the infants' responses to words versus part-words (trisyllabic sequences spanning word boundaries). The corpus was constructed so that test words and part-words were matched in frequency, but differed in their transitional probabilities. Infants showed reliable discrimination of words from part-words, thereby demonstrating rapid segmentation of continuous speech into words on the basis of transitional probabilities of syllable pairs.     

Learning words’ sounds before learning how words sound: 9-Month-olds use distinct objects as cues to categorize speech information

One of the central themes in the study of language acquisition is the gap between the linguistic knowledge that learners demonstrate, and the apparent inadequacy of linguistic input to support induction of this knowledge. One of the first linguistic abilities in the course of development to exemplify this problem is in speech perception: specifically, learning the sound system of one’s native language. Native-language sound systems are defined by meaningful contrasts among words in a language, yet infants learn these sound patterns before any significant numbers of words are acquired. Previous approaches to this learning problem have suggested that infants can learn phonetic categories from statistical analysis of auditory input, without regard to word referents. Experimental evidence presented here suggests instead that young infants can use visual cues present in word-labeling situations to categorize phonetic information. In Experiment 1, 9-month-old English-learning infants failed to discriminate two non-native phonetic categories, establishing baseline performance in a perceptual discrimination task. In Experiment 2, these infants succeeded at discrimination after watching contrasting visual cues (i.e., videos of two novel objects) paired consistently with the two non-native phonetic categories. In Experiment 3, these infants failed at discrimination after watching the same visual cues, but paired inconsistently with the two phonetic categories. At an age before which memory of word labels is demonstrated in the laboratory, 9-month-old infants use contrastive pairings between objects and sounds to influence their phonetic sensitivity. Phonetic learning may have a more functional basis than previous statistical learning mechanisms assume: infants may use cross-modal associations inherent in social contexts to learn native-language phonetic categories.     

Speech segmentation is facilitated by visual cues

Evidence from infant studies indicates that language learning can be facilitated by multimodal cues. We extended this observation to adult language learning by studying the effects of simultaneous visual cues (nonassociated object images) on speech segmentation performance. Our results indicate that segmentation of new words from a continuous speech stream is facilitated by simultaneous visual input that it is presented at or near syllables that exhibit the low transitional probability indicative of word boundaries. This indicates that temporal audio-visual contiguity helps in directing attention to word boundaries at the earliest stages of language learning. Off-boundary or arrhythmic picture sequences did not affect segmentation performance, suggesting that the language learning system can effectively disregard noninformative visual information. Detection of temporal contiguity between multimodal stimuli may be useful in both infants and second-language learners not only for facilitating speech segmentation, but also for detecting word–object relationships in natural environments.     

The link between statistical segmentation and word learning in adults

Many studies have shown that listeners can segment words from running speech based on conditional probabilities of syllable transitions, suggesting that this statistical learning could be a foundational component of language learning. However, few studies have shown a direct link between statistical segmentation and word learning. We examined this possible link in adults by following a statistical segmentation exposure phase with an artificial lexicon learning phase. Participants were able to learn all novel object-label pairings, but pairings were learned faster when labels contained high probability (word-like) or non-occurring syllable transitions from the statistical segmentation phase than when they contained low probability (boundary-straddling) syllable transitions. This suggests that, for adults, labels inconsistent with expectations based on statistical learning are harder to learn than consistent or neutral labels. In contrast, a previous study found that infants learn consistent labels, but not inconsistent or neutral labels.     

Rapid word learning in 13- and 17-month-olds in a naturalistic two-word procedure: looking versus reaching measures

This study investigated infants’ rapid learning of two novel words using a preferential looking measure compared with a preferential reaching measure. In Experiment 1, 21 13-month-olds and 20 17-month-olds were given 12 novel label exposures (6 per trial) for each of two novel objects. Next, in the label comprehension tests, infants were shown both objects and were asked, “Where’s the [label]?” (looking preference) and then told, “Put the [label] in the basket” (reaching preference). Only the 13-month-olds showed rapid word learning on the looking measure; neither age group showed rapid word learning on the reaching measure. In Experiment 2, the procedure was repeated 24 h later with 10 participants per age group from Experiment 1. After a further 12 labels per object, both age groups now showed robust evidence of rapid word learning, but again only on the looking measure. This is the earliest looking-based evidence of rapid word learning in infants in a well-controlled (i.e., two-word) procedure; our failure to replicate previous reports of rapid word learning in 13-month-olds with a preferential reaching measure may be due to our use of more rigorous controls for object preferences. The superior performance of the younger infants on the looking measure in Experiment 1 was not straightforwardly predicted by existing theoretical accounts of word learning.     

Learning in reverse: Eight-month-old infants track backward transitional probabilities

Numerous recent studies suggest that human learners, including both infants and adults, readily track sequential statistics computed between adjacent elements. One such statistic, transitional probability, is typically calculated as the likelihood that one element predicts another. However, little is known about whether listeners are sensitive to the directionality of this computation. To address this issue, we tested 8-month-old infants in a word segmentation task, using fluent speech drawn from an unfamiliar natural language. Critically, test items were distinguished solely by their backward transitional probabilities. The results provide the first evidence that infants track backward statistics in fluent speech.     

Isolated words enhance statistical language learning in infancy

Infants are adept at tracking statistical regularities to identify word boundaries in pause-free speech. However, researchers have questioned the relevance of statistical learning mechanisms to language acquisition, since previous studies have used simplified artificial languages that ignore the variability of real language input. The experiments reported here embraced a key dimension of variability in infant-directed speech. English-learning infants (8-10 months) listened briefly to natural Italian speech that contained either fluent speech only or a combination of fluent speech and single-word utterances. Listening times revealed successful learning of the statistical properties of target words only when words appeared both in fluent speech and in isolation; brief exposure to fluent speech alone was not sufficient to facilitate detection of the words' statistical properties. This investigation suggests that statistical learning mechanisms actually benefit from variability in utterance length, and provides the first evidence that isolated words and longer utterances act in concert to support infant word segmentation.     

Why Choo‐Choo Is Better Than Train: The Role of Register‐Specific Words in Early Vocabulary Growth

Across languages, lexical items specific to infant‐directed speech (i.e., ‘baby‐talk words’) are characterized by a preponderance of onomatopoeia (or highly iconic words), diminutives, and reduplication. These lexical characteristics may help infants discover the referential nature of words, identify word referents, and segment fluent speech into words. If so, the amount of lexical input containing these properties should predict infants’ rate of vocabulary growth. To test this prediction, we tracked the vocabulary size in 47 English‐learning infants from 9 to 21 months and examined whether the patterns of growth can be related to measures of iconicity, diminutives, and reduplication in the lexical input at 9 months. Our analyses showed that both diminutives and reduplication in the input were associated with vocabulary growth, although measures of iconicity were not. These results are consistent with the hypothesis that phonological properties typical of lexical input in infant‐directed speech play a role in early vocabulary growth.     

Is early word-form processing stress-full? How natural variability supports recognition

In a series of studies, we examined how mothers naturally stress words across multiple mentions in speech to their infants and how this marking influences infants’ recognition of words in fluent speech. We first collected samples of mothers’ infant-directed speech using a technique that induced multiple repetitions of target words. Acoustic analyses revealed that mothers systematically alternated between emphatic and nonemphatic stress when talking to their infants. Using the headturn preference procedure, we then tested 7.5-month-old infants on their ability to detect familiarized bisyllabic words in fluent speech. Stress of target words (emphatic and nonemphatic) was systematically varied across familiarization and recognition phases of four experiments. Results indicated that, although infants generally prefer listening to words produced with emphatic stress, recognition was enhanced when the degree of emphatic stress at familiarization matched the degree of emphatic stress at recognition.     

Learning across languages: bilingual experience supports dual language statistical word segmentation

Bilingual acquisition presents learning challenges beyond those found in monolingual environments, including the need to segment speech in two languages. Infants may use statistical cues, such as syllable‐level transitional probabilities, to segment words from fluent speech. In the present study we assessed monolingual and bilingual 14‐month‐olds’ abilities to segment two artificial languages using transitional probability cues. In Experiment 1, monolingual infants successfully segmented the speech streams when the languages were presented individually. However, monolinguals did not segment the same language stimuli when they were presented together in interleaved segments, mimicking the language switches inherent to bilingual speech. To assess the effect of real‐world bilingual experience on dual language speech segmentation, Experiment 2 tested infants with regular exposure to two languages using the same interleaved language stimuli as Experiment 1. The bilingual infants in Experiment 2 successfully segmented the languages, indicating that early exposure to two languages supports infants’ abilities to segment dual language speech using transitional probability cues. These findings support the notion that early bilingual exposure prepares infants to navigate challenging aspects of dual language environments as they begin to acquire two languages.     

Twenty four-month-old infants’ interpretations of novel verbs and nouns in dynamic scenes

The current experiments address several concerns, both empirical and theoretical in nature, that have surfaced within the verb learning literature. They begin to reconcile what, until now, has been a large and largely unexplained gap between infants’ well-documented ability to acquire verbs in the natural course of their lives and their rather surprising failures to do so in many laboratory-based tasks. We presented 24-month-old infants with dynamic scenes (e.g., a man waving a balloon), and asked (a) whether infants could construe these scenes flexibly, noticing the consistent action (e.g., waving) as well as the consistent object (e.g., the balloon) and (b) whether their construals of the scenes were influenced by the grammatical form of a novel word used to describe them (verb or noun). We document that 24-month-olds’ representations of novel words are sufficiently precise to permit them to map novel verbs to event categories (e.g., waving events) and novel nouns to object categories (e.g., balloons). We also document the time-course underlying infants’ mapping of the novel words. These results beckon us to move beyond asking whether or not infants can represent verb meanings, and to consider instead the conditions that support successful verb learning in infants and young children.     

Testing the limits of statistical learning for word segmentation

Past research has demonstrated that infants can rapidly extract syllable distribution information from an artificial language and use this knowledge to infer likely word boundaries in speech. However, artificial languages are extremely simplified with respect to natural language. In this study, we ask whether infants’ ability to track transitional probabilities between syllables in an artificial language can scale up to the challenge of natural language. We do so by testing both 5.5‐ and 8‐month‐olds’ ability to segment an artificial language containing four words of uniform length (all CVCV) or four words of varying length (two CVCV, two CVCVCV). The transitional probability cues to word boundaries were held equal across the two languages. Both age groups segmented the language containing words of uniform length, demonstrating that even 5.5‐month‐olds are extremely sensitive to the conditional probabilities in their environment. However, neither age group succeeded in segmenting the language containing words of varying length, despite the fact that the transitional probability cues defining word boundaries were equally strong in the two languages. We conclude that infants’ statistical learning abilities may not be as robust as earlier studies have suggested.     

Infants’ statistical word segmentation in an artificial language is linked to both parental speech input and reported production abilities

Individual variability in infant's language processing is partly explained by environmental factors, like the quantity of parental speech input, as well as by infant‐specific factors, like speech production. Here, we explore how these factors affect infant word segmentation. We used an artificial language to ensure that only statistical regularities (like transitional probabilities between syllables) could cue word boundaries, and then asked how the quantity of parental speech input and infants’ babbling repertoire predict infants’ abilities to use these statistical cues. We replicated prior reports showing that 8‐month‐old infants use statistical cues to segment words, with a preference for part‐words over words (a novelty effect). Crucially, 8‐month‐olds with larger novelty effects had received more speech input at 4 months and had greater production abilities at 8 months. These findings establish for the first time that the ability to extract statistical information from speech correlates with individual factors in infancy, like early speech experience and language production. Implications of these findings for understanding individual variability in early language acquisition are discussed.     

(Non)words, (non)words, (non)words: evidence for a protolexicon during the first year of life

Previous research with artificial language learning paradigms has shown that infants are sensitive to statistical cues to word boundaries (Saffran, Aslin & Newport, 1996) and that they can use these cues to extract word‐like units (Saffran, 2001). However, it is unknown whether infants use statistical information to construct a receptive lexicon when acquiring their native language. In order to investigate this issue, we rely on the fact that besides real words a statistical algorithm extracts sound sequences that are highly frequent in infant‐directed speech but constitute nonwords. In three experiments, we use a preferential listening paradigm to test French‐learning 11‐month‐old infants' recognition of highly frequent disyllabic sequences from their native language. In Experiments 1 and 2, we use nonword stimuli and find that infants listen longer to high‐frequency than to low‐frequency sequences. In Experiment 3, we compare high‐frequency nonwords to real words in the same frequency range, and find that infants show no preference. Thus, at 11 months, French‐learning infants recognize highly frequent sound sequences from their native language and fail to differentiate between words and nonwords among these sequences. These results are evidence that they have used statistical information to extract word candidates from their input and stored them in a ‘protolexicon’, containing both words and nonwords.     

Object labeling influences infant phonetic learning and generalization

Different kinds of speech sounds are used to signify possible word forms in every language. For example, lexical stress is used in Spanish (/‘be.be/, ‘he/she drinks’ versus /be.’be/, ‘baby’), but not in French (/‘be.be/ and /be.’be/ both mean ‘baby’). Infants learn many such native language phonetic contrasts in their first year of life, likely using a number of cues from parental speech input. One such cue could be parents’ object labeling, which can explicitly highlight relevant contrasts. Here we ask whether phonetic learning from object labeling is abstract—that is, if learning can generalize to new phonetic contexts. We investigate this issue in the prosodic domain, as the abstraction of prosodic cues (like lexical stress) has been shown to be particularly difficult. One group of 10-month-old French-learners was given consistent word labels that contrasted on lexical stress (e.g., Object A was labeled /‘ma.bu/, and Object B was labeled /ma.’bu/). Another group of 10-month-olds was given inconsistent word labels (i.e., mixed pairings), and stress discrimination in both groups was measured in a test phase with words made up of new syllables. Infants trained with consistently contrastive labels showed an earlier effect of discrimination compared to infants trained with inconsistent labels. Results indicate that phonetic learning from object labeling can indeed generalize, and suggest one way infants may learn the sound properties of their native language(s).     

Social interaction facilitates word learning in preverbal infants: Word–object mapping and word segmentation

In natural settings, infants learn spoken language with the aid of a caregiver who explicitly provides social signals. Although previous studies have demonstrated that young infants are sensitive to these signals that facilitate language development, the impact of real-life interactions on early word segmentation and word–object mapping remains elusive. We tested whether infants aged 5–6 months and 9–10 months could segment a word from continuous speech and acquire a word–object relation in an ecologically valid setting. In Experiment 1, infants were exposed to a live tutor, while in Experiment 2, another group of infants were exposed to a televised tutor. Results indicate that both younger and older infants were capable of segmenting a word and learning a word–object association only when the stimuli were derived from a live tutor in a natural manner, suggesting that real-life interaction enhances the learning of spoken words in preverbal infants.     

How infants begin to extract words from speech

A crucial step for acquiring a native language vocabulary is the ability to segment words from fluent speech. English-learning infants first display some ability to segment words at about 7.5 months of age. However, their initial attempts at segmenting words only approximate those of fluent speakers of the language. In particular, 7.5-month-old infants are able to segment words that conform to the predominant stress pattern of English words. The ability to segment words with other stress patterns appears to require the use of other sources of information about word boundaries. By 10.5 months, English learners display sensitivity to additional cues to word boundaries such as statistical regularities, allophonic cues and phonotactic patterns. Infants’ word segmentation abilities undergo further development during their second year when they begin to link sound patterns with particular meanings. By 24 months, the speed and accuracy with which infants recognize words in fluent speech is similar to that of native adult listeners. This review describes how infants use multiple sources of information to locate word boundaries in fluent speech, thereby laying the foundations for language understanding.