Judging words by their covers and the company they keep: probabilistic cues support word learning

The effect of cue length and position on noticing and learning of determiner agreement pairings: Evidence from a cue-balanced artificial vocabulary learning task

The importance of cues in language learning has long been established and it is clear that cues are an essential part of both first language (L1) and second/additional language (L2/A) acquisition. The effects of cue reliability and frequency, along with the competition between cues have been shown to significantly impact learners' pace of acquisition of these language-specific patterns. However, natural languages do not allow for a clear picture of how the forms of cues themselves affect their perception, uptake, and generalizability. In this study, we developed an artificial vocabulary consisting of determiners and nouns. Within these nouns, completely reliable cues were developed and equally distributed as long and short cues over three possible positions: beginning, middle, or end. Through a word-pair learning study, we show that length and position of cues variably affects agreement accuracy, and that noticing of cues during training is less important for known words, and more important for novel ones when deciding on inter-word gender-like agreement.

Frequent vs. infrequent words shape toddlers' real-time sentence comprehension

We examined how noun frequency and the typicality of surrounding linguistic context contribute to children's real-time comprehension. Monolingual English-learning toddlers viewed pairs of pictures while hearing sentences with typical or atypical sentence frames (Look at the… vs. Examine the…), followed by nouns that were higher- or lower-frequency labels for a referent (horse vs. pony). Toddlers showed no significant differences in comprehension of nouns in typical and atypical sentence frames. However, they were less accurate in recognizing lower-frequency nouns, particularly among toddlers with smaller vocabularies. We conclude that toddlers can recognize nouns in diverse sentence contexts, but their representations develop gradually.

Statistical word segmentation: Anchoring learning across contexts

The present experiments were designed to assess infants' abilities to use syllable co-occurrence regularities to segment fluent speech across contexts. Specifically, we investigated whether 9-month-old infants could use statistical regularities in one speech context to support speech segmentation in a second context. Contexts were defined by different word sets representing contextual differences that might occur across conversations or utterances. This mimics the integration of information across multiple interactions within a single language, which is critical for language acquisition. In particular, we performed two experiments to assess whether a statistically segmented word could be used to anchor segmentation in a second, more challenging context, namely speech with variable word lengths. The results of Experiment 1 were consistent with past work suggesting that statistical learning may be hindered by speech with word-length variability, which is inherent to infants' natural speech environments. In Experiment 2, we found that infants could use a previously statistically segmented word to support word segmentation in a novel, challenging context. We also present findings suggesting that this ability was associated with infants' early word knowledge but not their performance on a cognitive development assessment.

Kindergarteners Use Cross-Situational Statistics to Infer the Meaning of Grammatical Elements

Many studies demonstrate that detecting statistical regularities in linguistic input plays a key role in language acquisition. Yet, it is unclear to what extent statistical learning is involved in more naturalistic settings, when young children have to acquire meaningful grammatical elements. In the present study, we address these points, by investigating whether statistical learning is involved in acquiring a morpho-syntactic structure from input that resembles natural languages more closely. We exposed 50 kindergarteners (M = 5 years, 5 months) to a miniature language in which they had to learn a grammatical marker that expressed number, and which could only be acquired on the basis of the distributional properties in the input. Half of the children performed an attention check during the experiment. Results show that young children are able to learn this meaning. We found no clear evidence that facilitating attention to the input increases learning performance.

Distributional Lattices as a Model for Discovering Syntactic Categories in Child-Directed Speech

Distribution information plays an important role in word categorization. In this paper, we present a novel distributional model, distributional lattices to discover syntactic categories in child directed speech. A distributional lattice is a hierarchy formed by closed sets of words that are distributionally similar. Such a hierarchy is potentially useful for capturing syntactic categories by clustering words with associate patterns they occur in. In order to empirically support the suggestion that the distributional lattice is effective at categorizing words, we present a distributional lattice analysis of the Brent corpus of child-directed speech. The results show that distributional lattices are able to yield extremely accurate syntactic categories.

Word Segmentation Cues in German Child-Directed Speech: A Corpus Analysis

To acquire language, infants must learn to segment words from running speech. A significant body of experimental research shows that infants use multiple cues to do so; however, little research has comprehensively examined the distribution of such cues in naturalistic speech. We conducted a comprehensive corpus analysis of German child-directed speech (CDS) using data from the Child Language Data Exchange System (CHILDES) database, investigating the availability of word stress, transitional probabilities (TPs), and lexical and sublexical frequencies as potential cues for word segmentation. Seven hours of data (~15,000 words) were coded, representing around an average day of speech to infants. The analysis revealed that for 97% of words, primary stress was carried by the initial syllable, implicating stress as a reliable cue to word onset in German CDS. Word identity was also marked by TPs between syllables, which were higher within than between words, and higher for backwards than forwards transitions. Words followed a Zipfian-like frequency distribution, and over two-thirds of words (78%) were monosyllabic. Of the 50 most frequent words, 82% were function words, which accounted for 47% of word tokens in the entire corpus. Finally, 15% of all utterances comprised single words. These results give rich novel insights into the availability of segmentation cues in German CDS, and support the possibility that infants draw on multiple converging cues to segment their input. The data, which we make openly available to the research community, will help guide future experimental investigations on this topic.

Exploring the "anchor word" effect in infants: Segmentation and categorisation of speech with and without high frequency words

High frequency words play a key role in language acquisition, with recent work suggesting they may serve both speech segmentation and lexical categorisation. However, it is not yet known whether infants can detect novel high frequency words in continuous speech, nor whether they can use them to help learning for segmentation and categorisation at the same time. For instance, when hearing "you eat the biscuit", can children use the high-frequency words "you" and "the" to segment out "eat" and "biscuit", and determine their respective lexical categories? We tested this in two experiments. In Experiment 1, we familiarised 12-month-old infants with continuous artificial speech comprising repetitions of target words, which were preceded by high-frequency marker words that distinguished the targets into two distributional categories. In Experiment 2, we repeated the task using the same language but with additional phonological cues to word and category structure. In both studies, we measured learning with head-turn preference tests of segmentation and categorisation, and compared performance against a control group that heard the artificial speech without the marker words (i.e., just the targets). There was no evidence that high frequency words helped either speech segmentation or grammatical categorisation. However, segmentation was seen to improve when the distributional information was supplemented with phonological cues (Experiment 2). In both experiments, exploratory analysis indicated that infants' looking behaviour was related to their linguistic maturity (indexed by infants' vocabulary scores) with infants with high versus low vocabulary scores displaying novelty and familiarity preferences, respectively. We propose that high-frequency words must reach a critical threshold of familiarity before they can be of significant benefit to learning.

Non-adjacent dependency learning in infancy, and its link to language development

To acquire language, infants must learn how to identify words and linguistic structure in speech. Statistical learning has been suggested to assist both of these tasks. However, infants' capacity to use statistics to discover words and structure together remains unclear. Further, it is not yet known how infants'  statistical learning ability relates to their language development. We trained 17-month-old infants on an artificial language comprising non-adjacent dependencies, and examined their looking times on tasks assessing sensitivity to words and structure using an eye-tracked head-turn-preference paradigm. We measured infants' vocabulary size using a Communicative Development Inventory (CDI) concurrently and at 19, 21, 24, 25, 27, and 30 months to relate performance to language development. Infants could segment the words from speech, demonstrated by a significant difference in looking times to words versus part-words. Infants' segmentation performance was significantly related to their vocabulary size (receptive and expressive) both currently, and over time (receptive until 24 months, expressive until 30 months), but was not related to the rate of vocabulary growth. The data also suggest infants may have developed sensitivity to generalised structure, indicating similar statistical learning mechanisms may contribute to the discovery of words and structure in speech, but this was not related to vocabulary size.

Statistical Learning and Social Competency: The Mediating Role of Language

The current study sought to examine the contribution of auditory and visual statistical learning on language and social competency abilities as well as whether decreased statistical learning abilities are related to increased autistic traits. To answer these questions, participants' (N = 95) auditory and visual statistical learning abilities, language, social competency, and level of autistic traits were assessed. Although the relationships observed were relatively small in magnitude, our results demonstrated that visual statistical learning related to language and social competency abilities and that auditory learning was more related to autism symptomatology than visual statistical learning. Furthermore, the relationship between visual statistical learning and social competency was mediated by language comprehension abilities, suggesting that impairments in statistical learning may cascade into impairments in language and social abilities.

Individual differences in non-adjacent statistical dependency learning in infants

There is considerable controversy over the factors that shape infants' developing knowledge of grammar. Work with artificial languages suggests that infants' ability to track statistical regularities within the speech they hear could, in principle, support grammatical development. However, little work has tested whether infants' performance on laboratory tasks reflects factors that are relevant in real-world language learning. Here we tested whether the language that infants hear at home, and their receptive language skills, predict their performance on tasks assessing the ability to learn non-adjacent statistical dependencies (NADs) at 15 months, and whether that in turn predicts sensitivity to native-language NADs at 18 months. We found evidence for some (though not all) of these relations, and primarily for females. The results suggest that performance on the artificial language-learning task reveals something about the mechanisms of grammatical development, and that females and males may be learning NADs differently.

Semantic Memory and the Hippocampus: Revisiting, Reaffirming, and Extending the Reach of Their Critical Relationship

Since Tulving proposed a distinction in memory between semantic and episodic memory, considerable effort has been directed towards understanding their similar and unique features. Of particular interest has been the extent to which semantic and episodic memory have a shared dependence on the hippocampus. In contrast to the definitive evidence for the link between hippocampus and episodic memory, the role of the hippocampus in semantic memory has been a topic of considerable debate. This debate stems, in part, from highly variable reports of new semantic memory learning in amnesia ranging from profound impairment to full preservation, and various degrees of deficit and ability in between. More recently, a number of significant advances in experimental methods have occurred, alongside new provocative data on the role of the hippocampus in semantic memory, making this an ideal moment to revisit this debate, to re-evaluate data, methods, and theories, and to synthesize new findings. In line with these advances, this review has two primary goals. First, we provide a historical lens with which to reevaluate and contextualize the literature on semantic memory and the hippocampus. The second goal of this review is to provide a synthesis of new findings on the role of the hippocampus and semantic memory. With the perspective of time and this critical review, we arrive at the interpretation that the hippocampus does indeed make necessary contributions to semantic memory. We argue that semantic memory, like episodic memory, is a highly flexible, (re)constructive, relational and multimodal system, and that there is value in developing methods and materials that fully capture this depth and richness to facilitate comparisons to episodic memory. Such efforts will be critical in addressing questions regarding the cognitive and neural (inter)dependencies among forms of memory, and the role that these forms of memory play in support of cognition more broadly. Such efforts also promise to advance our understanding of how words, concepts, and meaning, as well as episodes and events, are instantiated and maintained in memory and will yield new insights into our two most quintessentially human abilities: memory and language.

Mark my words: High frequency marker words impact early stages of language learning

High frequency words have been suggested to benefit both speech segmentation and grammatical categorization of the words around them. Despite utilizing similar information, these tasks are usually investigated separately in studies examining learning. We determined whether including high frequency words in continuous speech could support categorization when words are being segmented for the first time. We familiarized learners with continuous artificial speech comprising repetitions of target words, which were preceded by high-frequency marker words. Crucially, marker words distinguished targets into 2 distributionally defined categories. We measured learning with segmentation and categorization tests and compared performance against a control group that heard the artificial speech without these marker words (i.e., just the targets, with no cues for categorization). Participants segmented the target words from speech in both conditions, but critically when the marker words were present, they influenced acquisition of word-referent mappings in a subsequent transfer task, with participants demonstrating better early learning for mappings that were consistent (rather than inconsistent) with the distributional categories. We propose that high-frequency words may assist early grammatical categorization, while speech segmentation is still being learned. (PsycINFO Database Record (c) 2019 APA, all rights reserved).

The Role of Statistical Learning in Understanding and Treating Spoken Language Outcomes in Deaf Children With Cochlear Implants

Purpose

Statistical learning-the ability to learn patterns in environmental input-is increasingly recognized as a foundational mechanism necessary for the successful acquisition of spoken language. Spoken language is a complex, serially presented signal that contains embedded statistical relations among linguistic units, such as phonemes, morphemes, and words, which represent the phonotactic and syntactic rules of language. In this review article, we first review recent work that demonstrates that, in typical language development, individuals who display better nonlinguistic statistical learning abilities also show better performance on different measures of language. We next review research findings that suggest that children who are deaf and use cochlear implants may have difficulties learning sequential input patterns, possibly due to auditory and/or linguistic deprivation early in development, and that the children who show better sequence learning abilities also display improved spoken language outcomes. Finally, we present recent findings suggesting that it may be possible to improve core statistical learning abilities with specialized training and interventions and that such improvements can potentially impact and facilitate the acquisition and processing of spoken language.

Method

We conducted a literature search through various online databases including PsychINFO and PubMed, as well as including relevant review articles gleaned from the reference sections of other review articles used in this review. Search terms included various combinations of the following: sequential learning, sequence learning, statistical learning, sequence processing, procedural learning, procedural memory, implicit learning, language, computerized training, working memory training, statistical learning training, deaf, deafness, hearing impairment, hearing impaired, DHH, hard of hearing, cochlear implant(s), hearing aid(s), and auditory deprivation. To keep this review concise and clear, we limited inclusion to the foundational and most recent (2005-2018) relevant studies that explicitly included research or theoretical perspectives on statistical or sequential learning. We here summarize and synthesize the most recent and relevant literature to understanding and treating language delays in children using cochlear implants through the lens of statistical learning.

Conclusions

We suggest that understanding how statistical learning contributes to spoken language development is important for understanding some of the difficulties that children who are deaf and use cochlear implants might face and argue that it may be beneficial to develop novel language interventions that focus specifically on improving core foundational statistical learning skills.

Distributional Cues to Language Learning in Children With Intellectual Disabilities

Purpose

In typical development, distributional cues-patterns in input-are related to language acquisition processes. Statistical and implicit learning refer to the utilization of such cues. In children with intellectual disability, much less is known about the extent to which distributional cues are harnessed in mechanisms of language learning.

Method

This tutorial presents what is known about the process of language learning in children with language impairments associated with different sources of intellectual disability: Williams syndrome, autism spectrum disorder, Down syndrome, and fragile X syndrome.

Results

A broad view is taken on distributional cues relevant to language learning, including statistical learning (e.g., transitional probabilities) and other patterns that support lexical acquisition (e.g., sensitivities to sound patterns, cross-situational word learning) or relate to syntactic development (e.g., nonadjacent dependencies).

Conclusions

Critical gaps in the literature are highlighted. Research in this area is especially limited for Down syndrome and fragile X syndrome. Future directions for taking learning theories into account in interventions for children with intellectual disability are discussed, with a focus on the importance of language input.

Infant statistical-learning ability is related to real-time language processing

Infants are adept at learning statistical regularities in artificial language materials, suggesting that the ability to learn statistical structure may support language development. Indeed, infants who perform better on statistical learning tasks tend to be more advanced in parental reports of infants' language skills. Work with adults suggests that one way statistical learning ability affects language proficiency is by facilitating real-time language processing. Here we tested whether 15-month-olds' ability to learn sequential statistical structure in artificial language materials is related to their ability to encode and interpret native-language speech. Specifically, we tested their ability to learn sequential structure among syllables (Experiment 1) and words (Experiment 2), as well as their ability to encode familiar English words in sentences. The results suggest that infants' ability to learn sequential structure among syllables is related to their lexical-processing efficiency, providing continuity with findings from children and adults, though effects were modest.

When Meaning Is Not Enough: Distributional and Semantic Cues to Word Categorization in Child Directed Speech

One of the most important tasks in first language development is assigning words to their grammatical category. The Semantic Bootstrapping Hypothesis postulates that, in order to accomplish this task, children are guided by a neat correspondence between semantic and grammatical categories, since nouns typically refer to objects and verbs to actions. It is this correspondence that guides children's initial word categorization. Other approaches, on the other hand, suggest that children might make use of distributional cues and word contexts to accomplish the word categorization task. According to such approaches, the Semantic Bootstrapping assumption offers an important limitation, as it might not be true that all the nouns that children hear refer to specific objects or people. In order to explore that, we carried out two studies based on analyses of children's linguistic input. We analyzed child-directed speech addressed to four children under the age of 2;6, taken from the CHILDES database. The corpora were selected from the Manchester corpus. The corpora from the four selected children contained a total of 10,681 word types and 364,196 word tokens. In our first study, discriminant analyses were performed using semantic cues alone. The results show that many of the nouns found in parents' speech do not relate to specific objects and that semantic information alone might not be sufficient for successful word categorization. Given that there must be an additional source of information which, alongside with semantics, might assist young learners in word categorization, our second study explores the availability of both distributional and semantic cues in child-directed speech. Our results confirm that this combination might yield better results for word categorization. These results are in line with theories that suggest the need for an integration of multiple cues from different sources in language development.

Individual Differences in Statistical Learning Predict Children's Comprehension of Syntax

Variability in children's language acquisition is likely due to a number of cognitive and social variables. The current study investigated whether individual differences in statistical learning (SL), which has been implicated in language acquisition, independently predicted 6- to 8-year-old's comprehension of syntax. Sixty-eight (N = 68) English-speaking children completed a test of comprehension of four syntactic structures, a test of SL utilizing nonlinguistic visual stimuli, and several additional control measures. The results revealed that SL independently predicted comprehension of two syntactic structures that show considerable variability in this age range: passives and object relative clauses. These data suggest that individual differences in children's capacity for SL are associated with the acquisition of the syntax of natural languages.