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.     

A Bayesian framework for word segmentation: Exploring the effects of context

Since the experiments of Saffran et al. [Saffran, J., Aslin, R., & Newport, E. (1996). Statistical learning in 8-month-old infants. Science, 274, 1926-1928], there has been a great deal of interest in the question of how statistical regularities in the speech stream might be used by infants to begin to identify individual words. In this work, we use computational modeling to explore the effects of different assumptions the learner might make regarding the nature of words - in particular, how these assumptions affect the kinds of words that are segmented from a corpus of transcribed child-directed speech. We develop several models within a Bayesian ideal observer framework, and use them to examine the consequences of assuming either that words are independent units, or units that help to predict other units. We show through empirical and theoretical results that the assumption of independence causes the learner to undersegment the corpus, with many two- and three-word sequences (e.g. what’s that, do you, in the house) misidentified as individual words. In contrast, when the learner assumes that words are predictive, the resulting segmentation is far more accurate. These results indicate that taking context into account is important for a statistical word segmentation strategy to be successful, and raise the possibility that even young infants may be able to exploit more subtle statistical patterns than have usually been considered.     

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.     

The evolution of frequency distributions: Relating regularization to inductive biases through iterated learning

The regularization of linguistic structures by learners has played a key role in arguments for strong innate constraints on language acquisition, and has important implications for language evolution. However, relating the inductive biases of learners to regularization behavior in laboratory tasks can be challenging without a formal model. In this paper we explore how regular linguistic structures can emerge from language evolution by iterated learning, in which one person’s linguistic output is used to generate the linguistic input provided to the next person. We use a model of iterated learning with Bayesian agents to show that this process can result in regularization when learners have the appropriate inductive biases. We then present three experiments demonstrating that simulating the process of language evolution in the laboratory can reveal biases towards regularization that might not otherwise be obvious, allowing weak biases to have strong effects. The results of these experiments suggest that people tend to regularize inconsistent word-meaning mappings, and that even a weak bias towards regularization can allow regular languages to be produced via language evolution by iterated learning.     

Japanese Sound‐Symbolism Facilitates Word Learning in English‐Speaking Children

Sound‐symbolism is the nonarbitrary link between the sound and meaning of a word. Japanese‐speaking children performed better in a verb generalization task when they were taught novel sound‐symbolic verbs, created based on existing Japanese sound‐symbolic words, than novel nonsound‐symbolic verbs ( Imai, Kita, Nagumo, & Okada, 2008 ). A question remained as to whether the Japanese children had picked up regularities in the Japanese sound‐symbolic lexicon or were sensitive to universal sound‐symbolism. The present study aimed to provide support for the latter. In a verb generalization task, English‐speaking 3‐year‐olds were taught novel sound‐symbolic verbs, created based on Japanese sound‐symbolism, or novel nonsound‐symbolic verbs. English‐speaking children performed better with the sound‐symbolic verbs, just like Japanese‐speaking children. We concluded that children are sensitive to universal sound‐symbolism and can utilize it in word learning and generalization, regardless of their native language.     

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.     

Word learning is 'smart': evidence that conceptual information affects preschoolers' extension of novel words

We examined electrophysiological correlates of conscious change detection versus change blindness for equivalent displays. Observers had to detect any changes, across a visual interruption, between a pair of successive displays. Each display comprised grey circles on a background of alternate black and white stripes. Foreground changes arose when light-grey circles turned dark-grey and vice-versa. Physically stronger background changes arose when all black stripes turned white and vice-versa. Despite their physical strength, background changes were undetected unless attention was directed to them, whereas foreground changes were invariably seen. Event-related potentials revealed that the P300 component was suppressed for unseen background changes, as compared with the same changes when seen. This effect arose first over frontal sites, and then spread to parietal sites. These results extend recent fMRI findings that fronto-parietal activation is associated with conscious visual change detection, to reveal the timing of these neural correlates.     

What does syntax say about space? 2-year-olds use sentence structure to learn new prepositions

Children as young as two use sentence structure to learn the meanings of verbs. We probed the generality of sensitivity to sentence structure by moving to a different semantic and syntactic domain, spatial prepositions. Twenty-six-month-olds used sentence structure to determine whether a new word was an object-category name (This is a corp!) or a spatial-relational term (This is acorp my box!). We argue that children rely on the intimate relationship between nouns in sentences and semantic arguments of predicate terms: Noting that a new word takes noun arguments identifies the new word as a predicate term, and directs the child's attention to relations among its arguments.     

Two-year-olds can begin to acquire verb meanings in socially impoverished contexts

By two years of age, toddlers are adept at recruiting social, observational, and linguistic cues to discover the meanings of words. Here, we ask how they fare in impoverished contexts in which linguistic cues are provided, but no social or visual information is available. Novel verbs are presented in a stream of syntactically informative sentences, but the sentences are not embedded in a social context, and no visual access to the verb’s referent is provided until the test phase. The results provide insight into how toddlers may benefit from overhearing contexts in which they are not directly attending to the ambient speech, and in which no conversational context, visual referent, or child-directed conversation is available.     

Detailed behavioral analysis as a window into cross-situational word learning

Recent research has demonstrated that word learners can determine word-referent mappings by tracking co-occurrences across multiple ambiguous naming events. The current study addresses the mechanisms underlying this capacity to learn words cross-situationally. This replication and extension of Yu and Smith (2007) investigates the factors influencing both successful cross-situational word learning and mis-mappings. Item analysis and error patterns revealed that the co-occurrence structure of the learning environment as well as the context of the testing environment jointly affected learning across observations. Learners also adopted an exclusion strategy, which contributed conjointly with statistical tracking to performance. Implications for our understanding of the processes underlying cross-situational word learning are discussed.     

Social cues modulate the representations underlying cross-situational learning

Because children hear language in environments that contain many things to talk about, learning the meaning of even the simplest word requires making inferences under uncertainty. A cross-situational statistical learner can aggregate across naming events to form stable word-referent mappings, but this approach neglects an important source of information that can reduce referential uncertainty: social cues from speakers (e.g., eye gaze). In four large-scale experiments with adults, we tested the effects of varying referential uncertainty in cross-situational word learning using social cues. Social cues shifted learners away from tracking multiple hypotheses and towards storing only a single hypothesis (Experiments 1 and 2). In addition, learners were sensitive to graded changes in the strength of a social cue, and when it became less reliable, they were more likely to store multiple hypotheses (Experiment 3). Finally, learners stored fewer word-referent mappings in the presence of a social cue even when given the opportunity to visually inspect the objects for the same amount of time (Experiment 4). Taken together, our data suggest that the representations underlying cross-situational word learning of concrete object labels are quite flexible: In conditions of greater uncertainty, learners store a broader range of information.     

What's new? Children prefer novelty in referent selection

Determining the referent of a novel name is a critical task for young language learners. The majority of studies on children’s referent selection focus on manipulating the sources of information (linguistic, contextual and pragmatic) that children can use to solve the referent mapping problem. Here, we take a step back and explore how children’s endogenous biases towards novelty and their own familiarity with novel objects influence their performance in such a task. We familiarized 2-year-old children with previously novel objects. Then, on novel name referent selection trials children were asked to select the referent from three novel objects: two previously seen and one completely novel object. Children demonstrated a clear bias to select the most novel object. A second experiment controls for pragmatic responding and replicates this finding. We conclude, therefore, that children’s referent selection is biased by previous exposure and children’s endogenous bias to novelty.     

Infants rapidly learn word-referent mappings via cross-situational statistics

First word learning should be difficult because any pairing of a word and scene presents the learner with an infinite number of possible referents. Accordingly, theorists of children's rapid word learning have sought constraints on word-referent mappings. These constraints are thought to work by enabling learners to resolve the ambiguity inherent in any labeled scene to determine the speaker's intended referent at that moment. The present study shows that 12- and 14-month-old infants can resolve the uncertainty problem in another way, not by unambiguously deciding the referent in a single word-scene pairing, but by rapidly evaluating the statistical evidence across many individually ambiguous words and scenes.     

Fine-grained sensitivity to statistical information in adult word learning

A language learner trying to acquire a new word must often sift through many potential relations between particular words and their possible meanings. In principle, statistical information about the distribution of those mappings could serve as one important source of data, but little is known about whether learners can in fact track multiple word-referent mappings, and, if they do, the precision with which they can represent those statistics. To test this, two experiments contrasted a pair of possibilities: that learners encode the fine-grained statistics of mappings in the input - both high- and low-frequency mappings - or, alternatively, that only high frequency mappings are represented. Participants were briefly trained on novel word-novel object pairs combined with varying frequencies: some objects were paired with one word, other objects with multiple words with differing frequencies (ranging from 10% to 80%). Results showed that participants were exquisitely sensitive to very small statistical differences in mappings. The second experiment showed that word learners' representation of low frequency mappings is modulated as a function of the variability in the environment. Implications for Mutual Exclusivity and Bayesian accounts of word learning are discussed.     

Learning words from reliable and unreliable speakers

Three studies examined whether 3- and 4-year olds would trust a reliable speaker over an unreliable speaker when learning a new word and whether that trust would be reversed, and the word mapping revised, when a trusted speaker later proved unreliable. Study 1 indicated that 3- and 4-year olds trusted a reliable speaker over an unreliable speaker. Study 2 indicated that some 4-year olds reversed trust and revised a word mapping when a trusted speaker later proved unreliable. Study 3 indicated that those 4-year olds who reversed trust and revised the word mapping were likely to maintain the revision and tended to favor the previously reliable speaker over time. These results are discussed in terms of the role of speaker reliability in young children's word learning.