Co‐occurrence statistics as a language‐dependent cue for speech segmentation

To what extent can language acquisition be explained in terms of different associative learning mechanisms? It has been hypothesized that distributional regularities in spoken languages are strong enough to elicit statistical learning about dependencies among speech units. Distributional regularities could be a useful cue for word learning even without rich language‐specific knowledge. However, it is not clear how strong and reliable the distributional cues are that humans might use to segment speech. We investigate cross‐linguistic viability of different statistical learning strategies by analyzing child‐directed speech corpora from nine languages and by modeling possible statistics‐based speech segmentations. We show that languages vary as to which statistical segmentation strategies are most successful. The variability of the results can be partially explained by systematic differences between languages, such as rhythmical differences. The results confirm previous findings that different statistical learning strategies are successful in different languages and suggest that infants may have to primarily rely on non‐statistical cues when they begin their process of speech segmentation.     

‘Ideal learning’ of natural language: Positive results about learning from positive evidence

Gold's [1967. Language identification in the limit. Information and Control, 16, 447-474] celebrated work on learning in the limit has been taken, by many cognitive scientists, to have powerful negative implications for the learnability of language from positive data (i.e., from mere exposure to linguistic input). This provides one, of several, lines of argument that language acquisition must draw on other sources of information, including innate constraints on learning. We consider an ‘ideal learner’ that applies a Simplicity Principle to the problem of language acquisition. The Simplicity Principle chooses the hypothesis that provides the briefest representation of the available data—here, the data are the linguistic input to the child. The Simplicity Principle allows learning from positive evidence alone, given quite weak assumptions, in apparent contrast to results on language learnability in the limit (e.g., Gold, 1967). These results provide a framework for reconsidering the learnability of various aspects of natural language from positive evidence, which has been at the center of theoretical debate in research on language acquisition and linguistics.     

儿童早期词汇获得的跨语言/文化研究

婴儿词汇学习是国际语言发展研究的前沿领域, 但大多数研究都是以英语婴儿为研究对象。目前国内关于汉语婴儿早期语言发展研究处于起步阶段。由于汉语在词法、句法等方面具有明显的特殊性, 另外, 成人“言语输入”的语用习惯以及非言语线索都会影响婴儿早期词汇学习, 使得不同语言文化下的婴儿呈现不同的单词学习模式。本项目力图从跨语言视角考察汉语和英语婴儿的早期单词学习(包括单词的理解和产生)以及促进婴儿语言发展的成人言语和非言语输入特征。研究将综合采用实验室实验、半结构化实验室观察和量表测量等研究方法, 利用新的研究技术(如习惯化和IPLP), 从多个角度探索婴儿词汇发展, 以及不同语言文化和个体环境对婴儿早期词汇学习的影响, 揭示词汇获得的跨语言一致性和特异性。研究结果有望对儿童的语言学习提供启示。     

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.     

Interactions between statistical and semantic information in infant language development

Infants can use statistical regularities to form rudimentary word categories (e.g. noun, verb), and to learn the meanings common to words from those categories. Using an artificial language methodology, we probed the mechanisms by which two types of statistical cues (distributional and phonological regularities) affect word learning. Because linking distributional cues vs. phonological information to semantics make different computational demands on learners, we also tested whether their use is related to language proficiency. We found that 22-month-old infants with smaller vocabularies generalized using phonological cues; however, infants with larger vocabularies showed the opposite pattern of results, generalizing based on distributional cues. These findings suggest that both phonological and distributional cues marking word categories promote early word learning. Moreover, while correlations between these cues are important to forming word categories, we found infants' weighting of these cues in subsequent word-learning tasks changes over the course of early language development.     

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.     

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.     

(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.     

Structural packaging in the input to language learning: Contributions of prosodic and morphological marking of phrases to the acquisition of language

The linguistic input to language learning is usually thought to consist of simple strings of words. We argue that input must also include information about how words group into syntactic phrases. Natural languages regularly incorporate correlated cues to phrase structure, such as prosody, function words, and concord morphology. The claim that such cues are necessary for successful acquisition of syntax was tested in a series of miniature language learning experiments with adult subjects. In each experiment, when input included some cue marking the phrase structure of sentences, subjects were entirely successful in learning syntax; in contrast, when input lacked such a cue (but was otherwise identical), subjects failed to learn significant portions of syntax. Cues to phrase structure appear to facilitate learning by indicating to the learner those domains within which distributional analyses may be most efficiently pursued, thereby reducing the amount and complexity of required input data. More complex target systems place greater premiums on efficient analysis; hence, such cues may be even more crucial for acquisition of natural language syntax. We suggest that the finding that phrase structure cues are a necessary aspect of language input reflects the limited capacities of human language learners; languages may incorporate structural cues in part to circumvent such limitations and ensure successful acquisition.     

Conflicting Social Cues: Fourteen- and 24-Month-Old Infants' Reliance on Gaze and Pointing Cues in Word Learning

Language acquisition is a process embedded in social routines. Despite considerable attention in research to its social nature, little is known about developmental differences in the relative priority of certain social cues over others during early word learning. Employing an eye-tracking paradigm, we presented 14-month-old infants, 24-month-old infants, and adults with movies in which an actor repeatedly gazed at one and pointed to the other of two objects while presenting them with a novel word. The results show that the 14-month-old infants pay more attention to a model's eye gaze when learning to map a novel word to a referent, whereas 24-month-old infants and adults rely more on pointing cues. Our results provide evidence for a developmental change in the relative priority of pointing versus eye-gazing cues in language acquisition.     

Implicit statistical learning in language processing: Word predictability is the key

Fundamental learning abilities related to the implicit encoding of sequential structure have been postulated to underlie language acquisition and processing. However, there is very little direct evidence to date supporting such a link between implicit statistical learning and language. In three experiments using novel methods of assessing implicit learning and language abilities, we show that sensitivity to sequential structure – as measured by improvements to immediate memory span for structurally-consistent input sequences – is significantly correlated with the ability to use knowledge of word predictability to aid speech perception under degraded listening conditions. Importantly, the association remained even after controlling for participant performance on other cognitive tasks, including short-term and working memory, intelligence, attention and inhibition, and vocabulary knowledge. Thus, the evidence suggests that implicit learning abilities are essential for acquiring long-term knowledge of the sequential structure of language – i.e., knowledge of word predictability – and that individual differences on such abilities impact speech perception in everyday situations. These findings provide a new theoretical rationale linking basic learning phenomena to specific aspects of spoken language processing in adults, and may furthermore indicate new fruitful directions for investigating both typical and atypical language development.     

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.     

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.     

口语加工中的词语切分线索

词是语言的基本结构单位, 对词语进行切分是语言加工的重要步骤。口语语流中的切分线索来自于语音、语义和语法三个方面。语音线索包括概率信息、音位配列规则和韵律信息, 韵律信息中还包括词重音、时长和音高等内容, 这些线索的使用在接触语言的早期阶段就逐渐被个体所掌握, 而且在不同的语言背景下有一定的特异性。语法和语义线索属于较高级的线索机制, 主要作用于词语切分过程的后期。后续研究应从语言的毕生发展和语言的特异性两个方面考察口语语言加工中的词语切分线索。     

A Large‐Scale Analysis of Variance in Written Language

The collection of very large text sources has revolutionized the study of natural language, leading to the development of several models of language learning and distributional semantics that extract sophisticated semantic representations of words based on the statistical redundancies contained within natural language (e.g., Griffiths, Steyvers, & Tenenbaum, 2007 ; Jones & Mewhort, 2007 ; Landauer & Dumais, 1997 ; Mikolov, Sutskever, Chen, Corrado, & Dean, 2013 ). The models treat knowledge as an interaction of processing mechanisms and the structure of language experience. But language experience is often treated agnostically. We report a distributional semantic analysis that shows written language in fiction books varies appreciably between books from the different genres, books from the same genre, and even books written by the same author. Given that current theories assume that word knowledge reflects an interaction between processing mechanisms and the language environment, the analysis shows the need for the field to engage in a more deliberate consideration and curation of the corpora used in computational studies of natural language processing.     

Age and experience shape developmental changes in the neural basis of language-related learning

Very little is known about the neural underpinnings of language learning across the lifespan and how these might be modified by maturational and experiential factors. Building on behavioral research highlighting the importance of early word segmentation (i.e. the detection of word boundaries in continuous speech) for subsequent language learning, here we characterize developmental changes in brain activity as this process occurs online, using data collected in a mixed cross-sectional and longitudinal design. One hundred and fifty-six participants, ranging from age 5 to adulthood, underwent functional magnetic resonance imaging (fMRI) while listening to three novel streams of continuous speech, which contained either strong statistical regularities, strong statistical regularities and speech cues, or weak statistical regularities providing minimal cues to word boundaries. All age groups displayed significant signal increases over time in temporal cortices for the streams with high statistical regularities; however, we observed a significant right-to-left shift in the laterality of these learning-related increases with age. Interestingly, only the 5- to 10-year-old children displayed significant signal increases for the stream with low statistical regularities, suggesting an age-related decrease in sensitivity to more subtle statistical cues. Further, in a sample of 78 10-year-olds, we examined the impact of proficiency in a second language and level of pubertal development on learning-related signal increases, showing that the brain regions involved in language learning are influenced by both experiential and maturational factors.     

Visual statistical learning in infancy: evidence for a domain general learning mechanism

The rapidity with which infants come to understand language and events in their surroundings has prompted speculation concerning innate knowledge structures that guide language acquisition and object knowledge. Recently, however, evidence has emerged that by 8 months, infants can extract statistical patterns in auditory input that are based on transitional probabilities defining the sequencing of the input's components (Science 274 (1996) 1926). This finding suggests powerful learning mechanisms that are functional in infancy, and raises questions about the domain generality of such mechanisms. We habituated 2-, 5-, and 8-month-old infants to sequences of discrete visual stimuli whose ordering followed a statistically predictable pattern. The infants subsequently viewed the familiar pattern alternating with a novel sequence of identical stimulus components, and exhibited significantly greater interest in the novel sequence at all ages. These results provide support for the likelihood of domain general statistical learning in infancy, and imply that mechanisms designed to detect structure inherent in the environment may play an important role in cognitive development.     

Mapping Word to World in ASL: Evidence from a Human Simulation Paradigm

Across languages, children map words to meaning with great efficiency, despite a seemingly unconstrained space of potential mappings. The literature on how children do this is primarily limited to spoken language. This leaves a gap in our understanding of sign language acquisition, because several of the hypothesized mechanisms that children use are visual (e.g., visual attention to the referent), and sign languages are perceived in the visual modality. Here, we used the Human Simulation Paradigm in American Sign Language (ASL) to determine potential cues to word learning. Sign-naïve adult participants viewed video clips of parent–child interactions in ASL, and at a designated point, had to guess what ASL sign the parent produced. Across two studies, we demonstrate that referential clarity in ASL interactions is characterized by access to information about word class and referent presence (for verbs), similarly to spoken language. Unlike spoken language, iconicity is a cue to word meaning in ASL, although this is not always a fruitful cue. We also present evidence that verbs are highlighted well in the input, relative to spoken English. The results shed light on both similarities and differences in the information that learners may have access to in acquiring signed versus spoken languages.     

Capacities underlying word learning

Children are strikingly good at learning the meanings of words. Current controversy focuses on the relative importance of different capacities in this learning process including principles of association, low-level attentional mechanisms, special word learning constraints, syntactic cues and theory of mind. We argue that children succeed at word learning because they possess certain conceptual biases about the external world, the ability to infer the referential intentions of others and an appreciation of syntactic cues to word meaning. Support for this view comes from studies exploring the phenomena of fast mapping, the whole object bias, the acquisition of names for entities belonging to different ontological kinds and the effect of lexical contrast. Word learning is not the result of a general associative learning process, nor does it involve specialized constraints. The ability to learn the meanings of words depends on a number of capacities, some of which are specific to language and unique to humans, others of which are potentially shared with other species.