Developmental differences in children's context-dependent word learning

In this study, 2.5-, 3-, and 4-year-olds (N = 108) participated in a novel noun generalization task in which background context was manipulated. During the learning phase of each trial, children were presented with exemplars in one or multiple background contexts. At the test, children were asked to generalize to a novel exemplar in either the same or a different context. The 2.5-year-olds’ performance was supported by matching contexts; otherwise, children in this age group demonstrated context dependent generalization. The 3-year-olds’ performance was also supported by matching contexts; however, children in this age group were aided by training in multiple contexts as well. Finally, the 4-year-olds demonstrated high performance in all conditions. The results are discussed in terms of the relationship between word learning and memory processes; both general memory development and memory developments specific to word learning (e.g., retention of linguistic labels) are likely to support word learning and generalization.     

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.     

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.     

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.     

Exclusion constraints facilitate statistical word learning

The roles of linguistic, cognitive, and social-pragmatic processes in word learning are well established. If statistical mechanisms also contribute to word learning, they must interact with these processes; however, there exists little evidence for such mechanistic synergy. Adults use co-occurrence statistics to encode speech-object pairings with detailed sensitivity in stochastic learning environments (Vouloumanos, 2008). Here, we replicate this statistical work with nonspeech sounds and compare the results with the previous speech studies to examine whether exclusion constraints contribute equally to the statistical learning of speech-object and nonspeech-object associations. In environments in which performance could benefit from exclusion, we find a learning advantage for speech over nonspeech, revealing an interaction between statistical and exclusion processes in associative word learning.     

Vowel categorization during word recognition in bilingual toddlers

Toddlers’ and preschoolers’ knowledge of the phonological forms of words was tested in Spanish-learning, Catalan-learning, and bilingual children. These populations are of particular interest because of differences in the Spanish and Catalan vowel systems: Catalan has two vowels in a phonetic region where Spanish has only one. The proximity of the Spanish vowel to the Catalan ones might pose special learning problems. Children were shown picture pairs; the target picture’s name was spoken correctly, or a vowel in the target word was altered. Altered vowels either contrasted with the usual vowel in Spanish and Catalan, or only in Catalan. Children’s looking to the target picture was used as a measure of word recognition. Monolinguals’ word recognition was hindered by within-language, but not non-native, vowel changes. Surprisingly, bilingual toddlers did not show sensitivity to changes in vowels contrastive only in Catalan. Among preschoolers, Catalan-dominant bilinguals but not Spanish-dominant bilinguals revealed mispronunciation sensitivity for the Catalan-only contrast. These studies reveal monolingual children’s robust knowledge of native-language vowel categories in words, and show that bilingual children whose two languages contain phonetically overlapping vowel categories may not treat those categories as separate in language comprehension.     

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.     

Causal relations drive young children's induction, naming, and categorization

A number of recent models and experiments have suggested that evidence of early category-based induction is an artifact of perceptual cues provided by experimenters. We tested these accounts against the prediction that different relations (causal versus non-causal) determine the types of perceptual similarity by which children generalize. Young children were asked to label, to infer novel properties, and to project future appearances of a novel animal that varied in two opposite respects: (1) how much it looked like another animal whose name and properties were known, and (2) how much its parents looked like parents of another animal whose name and properties were known. When exemplar origins were known, children generalized to exemplars with similar origins rather than with similar appearances; when origins were unknown, children generalized to exemplars with similar appearances. Results indicate even young children possess the cognitive control to choose the similarities that best predict accurate generalizations.     

The role of novelty in early word learning

What mechanism implements the mutual exclusivity bias to map novel labels to objects without names? Prominent theoretical accounts of mutual exclusivity (e.g., Markman, 1989, 1990 ) propose that infants are guided by their knowledge of object names. However, the mutual exclusivity constraint could be implemented via monitoring of object novelty (see Merriman, Marazita, & Jarvis, 1995 ). We sought to discriminate between these contrasting explanations across two preferential looking experiments with 22‐month‐olds. In Experiment 1, infants viewed three objects: one name‐known, two name‐unknown. Of the two name‐unknown objects, one was novel, and the other had been previously familiarized. The infants responded to hearing a novel label by increasing attention only to the novel, name‐unknown object. In a second experiment in which the name‐known object was absent, a novel label increased infants’ attention to a novel object beyond baseline preference for novelty. The experiments provide clear evidence for a novelty‐based mechanism. However, differences in the time course of disambiguation across experiments suggest that novelty processing may be influenced by contextual factors.     

Using variability to guide dimensional weighting: associative mechanisms in early word learning

At 14 months, children appear to struggle to apply their fairly well-developed speech perception abilities to learning similar sounding words (e.g., bih/dih; Stager & Werker, 1997). However, variability in nonphonetic aspects of the training stimuli seems to aid word learning at this age. Extant theories of early word learning cannot account for this benefit of variability. We offer a simple explanation for this range of effects based on associative learning. Simulations suggest that if infants encode both noncontrastive information (e.g., cues to speaker voice) and meaningful linguistic cues (e.g., place of articulation or voicing), then associative learning mechanisms predict these variability effects in early word learning. Crucially, this means that despite the importance of task variables in predicting performance, this body of work shows that phonological categories are still developing at this age, and that the structure of noninformative cues has critical influences on word learning abilities.     

The spacing effect in children's memory and category induction

The spacing effect describes the robust phenomenon whereby memory is enhanced when learning events are distributed, instead of being presented in succession. We investigated the effect of spacing on children's memory and category induction. Three-year-old children were presented with two tasks, a memory task and a category induction task. In the memory task, identical instances of an object were presented and then tested in a multiple choice test. In the category induction task, different instances of a category were presented and tested in a multiple choice test. In both tasks, presenting the instances in a spaced sequence resulted in more learning than presenting the instances in a massed sequence, despite the difficulty created by the spaced sequence. The spaced sequence increased the difficulty of the task by allowing children time to forget the previous instance during the spaced interval.     

An associative account of the development of word learning

Word learning is a notoriously difficult induction problem because meaning is underdetermined by positive examples. How do children solve this problem? Some have argued that word learning is achieved by means of inference: young word learners rely on a number of assumptions that reduce the overall hypothesis space by favoring some meanings over others. However, these approaches have difficulty explaining how words are learned from conversations or text, without pointing or explicit instruction. In this research, we propose an associative mechanism that can account for such learning. In a series of experiments, 4-year-olds and adults were presented with sets of words that included a single nonsense word (e.g. dax). Some lists were taxonomic (i.,e., all items were members of a given category), some were associative (i.e., all items were associates of a given category, but not members), and some were mixed. Participants were asked to indicate whether the nonsense word was an animal or an artifact. Adults exhibited evidence of learning when lists consisted of either associatively or taxonomically related items. In contrast, children exhibited evidence of word learning only when lists consisted of associatively related items. These results present challenges to several extant models of word learning, and a new model based on the distinction between syntagmatic and paradigmatic associations is proposed.     

A probabilistic computational model of cross-situational word learning

Words are the essence of communication: They are the building blocks of any language. Learning the meaning of words is thus one of the most important aspects of language acquisition: Children must first learn words before they can combine them into complex utterances. Many theories have been developed to explain the impressive efficiency of young children in acquiring the vocabulary of their language, as well as the developmental patterns observed in the course of lexical acquisition. A major source of disagreement among the different theories is whether children are equipped with special mechanisms and biases for word learning, or their general cognitive abilities are adequate for the task. We present a novel computational model of early word learning to shed light on the mechanisms that might be at work in this process. The model learns word meanings as probabilistic associations between words and semantic elements, using an incremental and probabilistic learning mechanism, and drawing only on general cognitive abilities. The results presented here demonstrate that much about word meanings can be learned from naturally occurring child-directed utterances (paired with meaning representations), without using any special biases or constraints, and without any explicit developmental changes in the underlying learning mechanism. Furthermore, our model provides explanations for the occasionally contradictory child experimental data, and offers predictions for the behavior of young word learners in novel situations.     

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.     

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.     

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.     

More is more: The relationship between vocabulary size and word extension

This study experimentally tested the relationship between children’s lexicon size and their ability to learn new words within the domain of color. We manipulated the size of 25 20-month-olds’ color lexicons by training them with two, four, or six different color words over the course of eight training sessions. We subsequently tested children’s ability to extend new color words to new instances. We found that training with a broader number of color words led to increased extension of new words. The results suggest that children’s learning history predicts their ability to learn new words within domains.     

Using Predictability for Lexical Segmentation

This study investigates a strategy based on predictability of consecutive sub‐lexical units in learning to segment a continuous speech stream into lexical units using computational modeling and simulations. Lexical segmentation is one of the early challenges during language acquisition, and it has been studied extensively through psycholinguistic experiments as well as computational methods. However, despite strong empirical evidence, the explicit use of predictability of basic sub‐lexical units in models of segmentation is underexplored. This paper presents an incremental computational model of lexical segmentation for exploring the usefulness of predictability for lexical segmentation. We show that the predictability cue is a strong cue for segmentation. Contrary to earlier reports in the literature, the strategy yields state‐of‐the‐art segmentation performance with an incremental computational model that uses only this particular cue in a cognitively plausible setting. The paper also reports an in‐depth analysis of the model, investigating the conditions affecting the usefulness of the strategy.     

Acquiring verbal reference: The interplay of cognitive,linguistic, and general learning capacities

Verbal reference is the ability to use language to communicate about objects, events, or ideas, even if they are not witnessed directly, such as past events or faraway places. It rests on a three-way link between words, their referents, and mental representations of those referents. A foundational human capacity, verbal reference extends the communicative power of language beyond the here-and-now, enabling access to language-mediated learning and thus fueling cognitive development. In the current review, we consider how and when verbal reference develops. The existing literature suggests that verbal reference emerges around infants’ first birthdays and becomes increasingly robust by their second. In discussing the powerful developmental advantages of acquiring verbal reference we propose that this achievement requires a dynamic interplay among infants’ cognitive and language development, fueled by general learning capacities. We close by describing new research directions, aimed at advancing our understanding of how verbal reference emerges.