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.     

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.     

The neural correlates of statistical learning in a word segmentation task: An fMRI study

Functional magnetic resonance imaging (fMRI) was used to assess neural activation as participants learned to segment continuous streams of speech containing syllable sequences varying in their transitional probabilities. Speech streams were presented in four runs, each followed by a behavioral test to measure the extent of learning over time. Behavioral performance indicated that participants could discriminate statistically coherent sequences (words) from less coherent sequences (partwords). Individual rates of learning, defined as the difference in ratings for words and partwords, were used as predictors of neural activation to ask which brain areas showed activity associated with these measures. Results showed significant activity in the pars opercularis and pars triangularis regions of the left inferior frontal gyrus (LIFG). The relationship between these findings and prior work on the neural basis of statistical learning is discussed, and parallels to the frontal/subcortical network involved in other forms of implicit sequence learning are considered.     

Cross-language word segmentation by 9-month-olds

Dutch-learning and English-learning 9-month-olds were tested, using the Headturn Preference Procedure, for their ability to segment Dutch words with strong/weak stress patterns from fluent Dutch speech. This prosodic pattern is highly typical for words of both languages. The infants were familiarized with pairs of words and then tested on four passages, two that included the familiarized words and two that did not. Both the Dutch- and the English-learning infants gave evidence of segmenting the targets from the passages, to an equivalent degree. Thus, English-learning infants are able to extract words from fluent speech in a language that is phonetically different from English. We discuss the possibility that this cross-language segmentation ability is aided by the similarity of the typical rhythmic structure of Dutch and English words.     

New evidence for chunk-based models in word segmentation

There is large evidence that infants are able to exploit statistical cues to discover the words of their language. However, how they proceed to do so is the object of enduring debates. The prevalent position is that words are extracted from the prior computation of statistics, in particular the transitional probabilities between syllables. As an alternative, chunk-based models posit that the sensitivity to statistics results from other processes, whereby many potential chunks are considered as candidate words, then selected as a function of their relevance. These two classes of models have proven to be difficult to dissociate. We propose here a procedure, which leads to contrasted predictions regarding the influence of a first language, L1, on the segmentation of a second language, L2. Simulations run with PARSER (Perruchet & Vinter, 1998), a chunk-based model, predict that when the words of L1 become word-external transitions of L2, learning of L2 should be depleted until reaching below chance level, at least before extensive exposure to L2 reverses the effect. In the same condition, a transitional-probability based model predicts above-chance performance whatever the duration of exposure to L2. PARSER's predictions were confirmed by experimental data: Performance on a two-alternative forced choice test between words and part-words from L2 was significantly below chance even though part-words were less cohesive in terms of transitional probabilities than words.     

The beginnings of word segmentation in english-learning infants

A series of 15 experiments was conducted to explore English-learning infants' capacities to segment bisyllabic words from fluent speech. The studies in Part I focused on 7.5 month olds' abilities to segment words with strong/weak stress patterns from fluent speech. The infants demonstrated an ability to detect strong/weak target words in sentential contexts. Moreover, the findings indicated that the infants were responding to the whole words and not to just their strong syllables. In Part II, a parallel series of studies was conducted examining 7.5 month olds' abilities to segment words with weak/strong stress patterns. In contrast with the results for strong/weak words, 7.5 month olds appeared to missegment weak/strong words. They demonstrated a tendency to treat strong syllables as markers of word onsets. In addition, when weak/strong words co-occurred with a particular following weak syllable (e.g., "guitar is"), 7.5 month olds appeared to misperceive these as strong/weak words (e.g., "taris"). The studies in Part III examined the abilities of 10.5 month olds to segment weak/strong words from fluent speech. These older infants were able to segment weak/strong words correctly from the various contexts in which they appeared. Overall, the findings suggest that English learners may rely heavily on stress cues when they begin to segment words from fluent speech. However, within a few months time, infants learn to integrate multiple sources of information about the likely boundaries of words in fluent speech.     

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.     

Frequency versus probability formats in statistical word problems

Three experiments examined people's ability to incorporate base rate information when judging posterior probabilities. Specifically, we tested the (Cosmides, L., & Tooby, J. (1996). Are humans good intuitive statisticians after all? Rethinking some conclusions from the literature on judgement under uncertainty. Cognition, 58, 1-73) conclusion that people's reasoning appears to follow Bayesian principles when they are presented with information in a frequency format, but not when information is presented as one case probabilities. First, we found that frequency formats were not generally associated with better performance than probability formats unless they were presented in a manner which facilitated construction of a set inclusion mental model. Second, we demonstrated that the use of frequency information may promote biases in the weighting of information. When participants are asked to express their judgements in frequency rather than probability format, they were more likely to produce the base rate as their answer, ignoring diagnostic evidence.     

Infants' sensitivity to allophonic cues for word segmentation

A series of four experiments was conducted to determine whether English-learning infants can use allophonic cues to word boundaries to segment words from fluent speech. Infants were familiarized with a pair of two-syllable items, such as nitrates and night rates and then were tested on their ability to detect these same words in fluent speech passages. The presence of allophonic cues to word boundaries did not help 9-month-olds to distinguish one of the familiarized words from an acoustically similar foil. Infants familiarized with nitrates were just as likely to listen to a passage about night rates as they were to listen to one about nitrates. Nevertheless, when the passages contained distributional cues that favored the extraction of the familiarized targets, 9-month-olds were able to segment these items from fluent speech. By the age of 10.5 months, infants were able to rely solely on allophonic cues to locate the familiarized target words in passages. We consider what implications these findings have for understanding how word segmentation skills develop.     

The role of talker-specific information in word segmentation by infants

Infants' representations of the sound patterns of words were explored by examining the effects of talker variability on the recognition of words in fluent speech. Infants were familiarized with isolated words (e.g., cup and dog) from 1 talker and then heard 4 passages produced by another talker, 2 of which included the familiarized words. At 7.5 months of age, infants attended longer to passages with the familiar words for materials produced by 2 female talkers or 2 male talkers but not for materials by a male and a female talker. These findings suggest a strong role for talker-voice similarity in infants' ability to generalize word tokens. By 10.5 months, infants could generalize different instances of the same word across talkers of the opposite sex. One implication of the present results is that infants' initial representations of the sound structure of words not only include phonetic information but also indexical properties relating to the vocal characteristics of particular talkers.     

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.     

Diminutives facilitate word segmentation in natural speech: Cross-linguistic evidence

Final-syllable invariance is characteristic of diminutives (e.g., doggie), which are a pervasive feature of the child-directed speech registers of many languages. Invariance in word endings has been shown to facilitate word segmentation (Kempe, Brooks, & Gillis, 2005) in an incidental-learning paradigm in which synthesized Dutch pseudonouns were used. To broaden the cross-linguistic evidence for this invariance effect and to increase its ecological validity, adult English speakers (n=276) were exposed to naturally spoken Dutch or Russian pseudonouns presented in sentence contexts. A forced choice test was given to assess target recognition, with foils comprising unfamiliar syllable combinations in Experiments 1 and 2 and syllable combinations straddling word boundaries in Experiment 3. A control group (n=210) received the recognition test with no prior exposure to targets. Recognition performance improved with increasing final-syllable rhyme invariance, with larger increases for the experimental group. This confirms that word ending invariance is a valid segmentation cue in artificial, as well as naturalistic, speech and that diminutives may aid segmentation in a number of languages.     

The role of partial knowledge in statistical word learning

A critical question about the nature of human learning is whether it is an all-or-none or a gradual, accumulative process. Associative and statistical theories of word learning rely critically on the later assumption: that the process of learning a word’s meaning unfolds over time. That is, learning the correct referent for a word involves the accumulation of partial knowledge across multiple instances. Some theories also make an even stronger claim: Partial knowledge of one word–object mapping can speed up the acquisition of other word–object mappings. We present three experiments that test and verify these claims by exposing learners to two consecutive blocks of cross-situational learning, in which half of the words and objects in the second block were those that participants failed to learn in Block 1. In line with an accumulative account, Re-exposure to these mis-mapped items accelerated the acquisition of both previously experienced mappings and wholly new word–object mappings. But how does partial knowledge of some words speed the acquisition of others? We consider two hypotheses. First, partial knowledge of a word could reduce the amount of information required for it to reach threshold, and the supra-threshold mapping could subsequently aid in the acquisition of new mappings. Alternatively, partial knowledge of a word’s meaning could be useful for disambiguating the meanings of other words even before the threshold of learning is reached. We construct and compare computational models embodying each of these hypotheses and show that the latter provides a better explanation of the empirical data.     

Item performance in visual word recognition

Standard factorial designs in psycholinguistics have been complemented recently by large-scale databases providing empirical constraints at the level of item performance. At the same time, the development of precise computational architectures has led modelers to compare item-level performance with item-level predictions. It has been suggested, however, that item performance includes a large amount of undesirable error variance that should be quantified to determine the amount of reproducible variance that models should account for. In the present study, we provide a simple and tractable statistical analysis of this issue. We also report practical solutions for estimating the amount of reproducible variance for any database that conforms to the additive decomposition of the variance. A new empirical database consisting of the word identification times of 140 participants on 120 words is then used to test these practical solutions. Finally, we show that increases in the amount of reproducible variance are accompanied by the detection of new sources of variance.     

Diminutives in child-directed speech supplement metric with distributional word segmentation cues

In two experiments, we explored whether diminutives (e.g.,birdie, Patty, bootie), which are characteristic of child-directed speech in many languages, aid word segmentation by regularizing stress patterns and word endings. In an implicit learning task, adult native speakers of English were exposed to a continuous stream of synthesized Dutch nonsense input comprising 300 randomized repetitions of six bisyllabic target nonwords. After exposure, the participants were given a forced choice recognition test to judge which strings had been present in the input. Experiment 1 demonstrated that English speakers used trochaic stress to isolate strings, despite being unfamiliar with Dutch phonotactics. Experiment 2 showed benefits from invariance introduced by affricates, which are typically found at onsets of final syllables in Dutch diminutives. Together, the results demonstrate that diminutives contain prosodic and distributional features that are beneficial for word segmentation.     

The effect of functional morphemes on word segmentation in preverbal infants

This study examines the role of functional morphemes in the earliest stage of lexical development. Recent research showed that prelinguistic infants can perceive functional morphemes. We inquire whether infants use frequent functors to segment potential word forms. French-learning 8-month-olds were familiarized to two utterance types: a novel noun following a functor, and another novel noun following a prosodically matched nonsense functor. After familiarization, infants' segmentation of the two nouns was assessed in a test phase presenting the nouns in isolation. Infants in Experiment 1 showed evidence of using both frequent functors des and mes (as opposed to the nonsense functor kes) to segment the nouns, suggesting also that they had specific representations of the functors. The infrequent functor vos in Experiment 2 did not facilitate segmentation. Frequency is thus a crucial factor. Our findings demonstrate that frequent functors can bootstrap infants into early lexical learning. Furthermore, the effect of functors for initial word segmentation is likely universal.     

Speech segmentation by statistical learning depends on attention

We addressed the hypothesis that word segmentation based on statistical regularities occurs without the need of attention. Participants were presented with a stream of artificial speech in which the only cue to extract the words was the presence of statistical regularities between syllables. Half of the participants were asked to passively listen to the speech stream, while the other half were asked to perform a concurrent task. In Experiment 1, the concurrent task was performed on a separate auditory stream (noises), in Experiment 2 it was performed on a visual stream (pictures), and in Experiment 3 it was performed on pitch changes in the speech stream itself. Invariably, passive listening to the speech stream led to successful word extraction (as measured by a recognition test presented after the exposure phase), whereas diverted attention led to a dramatic impairment in word segmentation performance. These findings demonstrate that when attentional resources are depleted, word segmentation based on statistical regularities is seriously compromised.     

Stress changes the representational landscape: evidence from word segmentation

Over the past couple of decades, research has established that infants are sensitive to the predominant stress pattern of their native language. However, the degree to which the stress pattern shapes infants' language development has yet to be fully determined. Whether stress is merely a cue to help organize the patterns of speech or whether it is an important part of the representation of speech sound sequences has still to be explored. Building on research in the areas of infant speech perception and segmentation, we asked how several months of exposure to the target language shapes infants' speech processing biases with respect to lexical stress. We hypothesize that infants represent stressed and unstressed syllables differently, and employed analyses of child-directed speech to show how this change to the representational landscape results in better distribution-based word segmentation as well as an advantage for stress-initial syllable sequences. A series of experiments then tested 9- and 7-month-old infants on their ability to use lexical stress without any other cues present to parse sequences from an artificial language. We found that infants adopted a stress-initial syllable strategy and that they appear to encode stress information as part of their proto-lexical representations. Together, the results of these studies suggest that stress information in the ambient language not only shapes how statistics are calculated over the speech input, but that it is also encoded in the representations of parsed speech sequences.     

中文阅读预视加工中的词频和预测性效应及其对词切分的启示:基于眼动的证据

研究采用眼动随动显示技术考察中文阅读预视加工中的词汇加工问题。前三项实验发现,剥夺预视加工的掩蔽条件、正确提示词n+1右侧边界的掩蔽条件以及不能提示词n+1右侧边界的掩蔽条件都不影响词频效应,说明中文读者对词n+1处文字的预视加工达不到词汇水平。实验4考察剥夺预视加工的掩蔽条件、提示词n+1右侧边界的掩蔽条件对预测性效应的影响,结果发现,剥夺预视加工完全消除预测性效应,提示词n+1右侧边界则减少预测性效应,说明对词汇的预期加工是中文读者切分词n+1的参考线索。综合4项实验结果可知,中文读者较难通过自下而上的文字识别切分词n+1,自上而下的词汇预期则是切分词n+1的加工形式。     

Infant word segmentation revisited: edge alignment facilitates target extraction

In a landmark study, Jusczyk and Aslin (1995) demonstrated that English-learning infants are able to segment words from continuous speech at 7.5 months of age. In the current study, we explored the possibility that infants segment words from the edges of utterances more readily than the middle of utterances. The same procedure was used as in Jusczyk and Aslin (1995); however, our stimuli were controlled for target word location and infants were given a shorter familiarization time to avoid ceiling effects. Infants were familiarized to one word that always occurred at the edge of an utterance (sentence-initial position for half of the infants and sentence-final position for the other half) and one word that always occurred in sentence-medial position. Our results demonstrate that infants segment words from the edges of an utterance more readily than from the middle of an utterance. In addition, infants segment words from utterance-final position just as readily as they segment words from utterance-initial position. Possible explanations for these results, as well as their implications for current models of the development of word segmentation, are discussed.