Segmentation by lexical subtraction in Hungarian speakers of second-language English

Using cross-modal form priming, we compared the use of stress and lexicality in the segmentation of spoken English by native English speakers (L1) and by native Hungarian speakers of second-language English (L2). For both language groups, lexicality was found to be an effective segmentation cue. That is, spoken disyllabic word fragments were stronger primes in a subsequent visual word recognition task when preceded by meaningful words than when preceded by nonwords: For example, the first two syllables of corridor were a more effective prime for visually presented corridor when heard in the phrase anythingcorri than in imoshingcorri. The stress pattern of the prime (strong–weak vs. weak–strong) did not affect the degree of priming. For L1 speakers, this supports previous findings about the preferential use of high-level segmentation strategies in clear speech. For L2 speakers, the lexical strategy was employed regardless of L2 proficiency level and instead of exploiting the consistent stress pattern of their native language. This is clear evidence for the primacy and robustness of segmentation by lexical subtraction even in individuals whose lexical knowledge is limited.     

Lexical and sublexical units in speech perception

Saffran, Newport, and Aslin (1996a) found that human infants are sensitive to statistical regularities corresponding to lexical units when hearing an artificial spoken language. Two sorts of segmentation strategies have been proposed to account for this early word-segmentation ability: bracketing strategies, in which infants are assumed to insert boundaries into continuous speech, and clustering strategies, in which infants are assumed to group certain speech sequences together into units ( Swingley, 2005 ). In the present study, we test the predictions of two computational models instantiating each of these strategies i.e., Serial Recurrent Networks: Elman, 1990 ; and Parser: Perruchet & Vinter, 1998 in an experiment where we compare the lexical and sublexical recognition performance of adults after hearing 2 or 10 min of an artificial spoken language. The results are consistent with Parser's predictions and the clustering approach, showing that performance on words is better than performance on part-words only after 10 min. This result suggests that word segmentation abilities are not merely due to stronger associations between sublexical units but to the emergence of stronger lexical representations during the development of speech perception processes.     

The use of time during lexical processing and segmentation: A review

Speech, by its very nature, is a time-based phenomenon. Speech sounds are temporally distributed, with the presentation of one sound roughly conditioned by the fading of the previous one. In this review, three classes of models are discussed with respect to the sequential nature of speech. It is argued that the three resulting conceptions of time are linked to the type of segmentation process proposed by these models to deal with speech continuity. In the first one, lexical activation is viewed as perfectly synchronized with the temporal deployment of speech. This type of model corresponds to the traditional left-to-right (proactive) account of lexical processing. Because serious segmentation problems exist for such an approach (e.g.,car andcard are embedded incardinal), the second type of model treats word recognition as the result of a mechanism that sometimes delays commitment on word identity beyond word offset. Lexical activation, instead of shadowing the unfolding of time, lags behind it until an unambiguous decision can be made. The temporarily unprocessed information is stored in a memory buffer. In the third approach, a prosodic cue (lexical stress) contributes actively to speech segmentation and lexical processing. Every stressed syllable encountered in the signal is postulated as a word onset and thus constitutes the starting point of lexical activation. However, with non-initial-stressed words, retroactive procedures going “back in time” must be used. Finally, the use of time (including proactive, delayed, and retroactive procedures) is discussed in light of cross-linguistic phonological differences.     

The secret is in the sound: from unsegmented speech to lexical categories

When learning language, young children are faced with many seemingly formidable challenges, including discovering words embedded in a continuous stream of sounds and determining what role these words play in syntactic constructions. We suggest that knowledge of phoneme distributions may play a crucial part in helping children segment words and determine their lexical category, and we propose an integrated model of how children might go from unsegmented speech to lexical categories. We corroborated this theoretical model using a two‐stage computational analysis of a large corpus of English child‐directed speech. First, we used transition probabilities between phonemes to find words in unsegmented speech. Second, we used distributional information about word edges – the beginning and ending phonemes of words – to predict whether the segmented words from the first stage were nouns, verbs, or something else. The results indicate that discovering lexical units and their associated syntactic category in child‐directed speech is possible by attending to the statistics of single phoneme transitions and word‐initial and final phonemes. Thus, we suggest that a core computational principle in language acquisition is that the same source of information is used to learn about different aspects of linguistic structure.     

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.     

Stress versus coarticulation: toward an integrated approach to explicit speech segmentation

Although word stress has been hailed as a powerful speech-segmentation cue, the results of 5 cross-modal fragment priming experiments revealed limitations to stress-based segmentation. Specifically, the stress pattern of auditory primes failed to have any effect on the lexical decision latencies to related visual targets. A determining factor was whether the onset of the prime was coarticulated with the preceding speech fragment. Uncoarticulated (i.e., concatenated) primes facilitated priming. Coarticulated ones did not. However, when the primes were presented in a background of noise, the pattern of results reversed, and a strong stress effect emerged: Stress-initial primes caused more pruning than non-initial-stress primes, regardless of the coarticulatory cues. The results underscore the role of coarticulation in the segmentation of clear speech and that of stress in impoverished listening conditions. More generally, they call for an integrated and signal-contingent approach to speech segmentation.     

German‐learning infants’ ability to detect unstressed closed‐class elements in continuous speech

The paper reports on two experiments with the head turn preference method which provide evidence that already at 7 to 9 months, but not yet at 6 months, German‐learning infants do recognize unstressed closed‐class lexical elements in continuous speech. These findings support the view that even preverbal children are able to compute at least phonological representations for closed‐class functional elements. They also suggest that these elements must be available to the language learning mechanisms of the child from very early on, allowing the child to make use of the distributional properties of closed‐class lexical elements for further top‐down analysis of the linguistic input, e.g. segmentation and syntactic categorization.     

Predication and cognitive context: Between minimalism and contextualism

In this paper, we suggest a strategy for modelling cognitive context within a truth‐conditional semantics, using Asher's model of predication. This allows us to introduce the notion of type presupposition intended as a lexical constraint to the composition of the truth‐conditional content. More specifically, we suggest that this model of predication produces a notion of truth‐conditional meaning where the cognitive context fixes a set of lexical restrictions and forced modifications. We conclude that this model might offer an intermediate position between Minimalism and Contextualism: an account that provides intuitive truth conditions within a formal semantic theory.     

Beliefs about what types of mechanisms produce random sequences

Although many researchers use Wagenaar's framework for understanding the factors that people use to determine whether a process is random, the framework has never undergone empirical scrutiny. This paper uses Wagenaar's framework as a starting point and examines the three properties of his framework—independence of events, fixed alternatives, and equiprobability. We find strong evidence to suggest that independence of events is indeed used as a cue toward randomness. Equiprobability has an effect on randomness judgments. However, it appears to work only in a limited role. Fixedness of alternatives is a complex construct that consists of multiple sub‐concepts. We find that each of these sub‐concepts influences randomness judgments, but that they exert forces in different directions. Stability of outcome ratios increases randomness judgments, while knowledge of outcome ratios decreases randomness judgments. Future directions for development of a functional framework for understanding perceptions of randomness are suggested. Copyright © 2008 John Wiley & Sons, Ltd.     

词素位置概率在中文阅读中的作用：词汇判断和眼动研究

中文词切分的认知机制一直是心理语言学关注的焦点问题之一,研究发现中文读者可使用词素位置概率等语言学线索帮助词切分,而首、尾词素位置概率的重要程度以往研究观点并不一致。本研究通过词汇判断和眼动实验,考察中文读者对首、尾词素位置概率的利用情况。实验1a和1b采用词汇判断任务,考察在不同词频条件下词首与词尾词素位置概率对词汇识别的影响。在错误率和反应时指标上,高频词条件下词首与词尾词素位置概率效应不显著;低频词条件下词首词素位置概率效应显著,词尾词素位置概率效应不显著。实验2a和2b采用句子阅读任务,考察在自然阅读情境中被试对词素位置概率的运用。在凝视时间、回视路径时间和总注视时间指标上,低频词条件下词首词素位置概率效应显著,词尾词素位置概率效应不显著。高频词条件下词首与词尾词素位置概率效应均不显著。词汇判断和眼动证据共同表明,词素位置概率信息是中文读者重要的语言词切分线索,且与词尾词素位置概率相比,词首词素位置概率在词汇切分与识别过程中发挥的作用更大。同时,词素位置概率线索的运用会受到词频的影响,研究结果支持复合词加工的混合通达表征模型。     

The Utility of Cognitive Plausibility in Language Acquisition Modeling: Evidence From Word Segmentation

The informativity of a computational model of language acquisition is directly related to how closely it approximates the actual acquisition task, sometimes referred to as the model's cognitive plausibility. We suggest that though every computational model necessarily idealizes the modeled task, an informative language acquisition model can aim to be cognitively plausible in multiple ways. We discuss these cognitive plausibility checkpoints generally and then apply them to a case study in word segmentation, investigating a promising Bayesian segmentation strategy. We incorporate cognitive plausibility by using an age‐appropriate unit of perceptual representation, evaluating the model output in terms of its utility, and incorporating cognitive constraints into the inference process. Our more cognitively plausible model shows a beneficial effect of cognitive constraints on segmentation performance. One interpretation of this effect is as a synergy between the naive theories of language structure that infants may have and the cognitive constraints that limit the fidelity of their inference processes, where less accurate inference approximations are better when the underlying assumptions about how words are generated are less accurate. More generally, these results highlight the utility of incorporating cognitive plausibility more fully into computational models of language acquisition.     

Infant word segmentation and childhood vocabulary development: a longitudinal analysis

Infants begin to segment novel words from speech by 7.5 months, demonstrating an ability to track, encode and retrieve words in the context of larger units. Although it is presumed that word recognition at this stage is a prerequisite to constructing a vocabulary, the continuity between these stages of development has not yet been empirically demonstrated. The goal of the present study is to investigate whether infant word segmentation skills are indeed related to later lexical development. Two word segmentation tasks, varying in complexity, were administered in infancy and related to childhood outcome measures. Outcome measures consisted of age‐normed productive vocabulary percentiles and a measure of cognitive development. Results demonstrated a strong degree of association between infant word segmentation abilities at 7 months and productive vocabulary size at 24 months. In addition, outcome groups, as defined by median vocabulary size and growth trajectories at 24 months, showed distinct word segmentation abilities as infants. These findings provide the first prospective evidence supporting the predictive validity of infant word segmentation tasks and suggest that they are indeed associated with mature word knowledge. A video abstract of this article can be viewed at http://www.youtube.com/watch?v=jxzLi5oLZQ8 .     

Estimating the effect of word predictability on eye movements in Chinese reading using latent semantic analysis and transitional probability

Latent semantic analysis (LSA) and transitional probability (TP), two computational methods used to reflect lexical semantic representation from large text corpora, were employed to examine the effects of word predictability on Chinese reading. Participants' eye movements were monitored, and the influence of word complexity (number of strokes), word frequency, and word predictability on different eye movement measures (first-fixation duration, gaze duration, and total time) were examined. We found influences of TP on first-fixation duration and gaze duration and of LSA on total time. The results suggest that TP reflects an early stage of lexical processing while LSA reflects a later stage.     

Verbalization of Decision Strategies in Multiple‐Cue Probabilistic Inference

In multiple‐cue probabilistic inference, people choose between alternatives based on several cues, each of which is differentially associated with an alternative's overall value. Various strategies have been proposed for probabilistic inference (e.g., weighted additive, tally, and take‐the‐best). These strategies differ in how many cue values they require to enact and in how they weight each cue. Do decision makers actually use any of these strategies? Ways to investigate this question include analyzing people's choices and the cues that they reveal. However, different strategies often predict the same decisions, and search behavior says nothing about whether or how people use the information that they acquire. In this research, we attempt to elucidate which strategies participants use in a multiple‐cue probabilistic inference task by examining verbal protocols, a high‐density source of process data. The promise of verbal data is in their utility for testing detailed information processing models. To that end, we apply protocol analysis in conjunction with computational simulations. We find converging evidence across outcome measures, search measures, and verbal reports that most participants use simplifying heuristics, namely take‐the‐best. Copyright © 2015 John Wiley & Sons, Ltd.     

词汇预测性对中文高、低阅读技能儿童眼动行为的影响

操纵目标词的预测性、词频和阅读技能水平,考察句子阅读中词汇预测性对高、低阅读技能儿童眼动行为的影响,揭示其在儿童阅读发展中的作用。结果显示：儿童对高预测词的跳读率更高、注视时间更短,且预测性与词频交互影响跳读率和注视时间;预测性对高阅读技能儿童早期的跳读率影响更大,而对低阅读技能儿童晚期的再阅读时间具有更大影响。结果表明：词汇预测性影响儿童阅读的眼动行为和词汇加工,且作用大小和发生时程受阅读技能调节。     

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.     

An interaction between prosody and statistics in the segmentation of fluent speech

Sensitivity to prosodic cues might be used to constrain lexical search. Indeed, the prosodic organization of speech is such that words are invariably aligned with phrasal prosodic edges, providing a cue to segmentation. In this paper we devise an experimental paradigm that allows us to investigate the interaction between statistical and prosodic cues to extract words from a speech stream. We provide evidence that statistics over the syllables are computed independently of prosody. However, we also show that trisyllabic sequences with high transition probabilities that straddle two prosodic constituents appear not to be recognized. Taken together, our findings suggest that prosody acts as a filter, suppressing possible word-like sequences that span prosodic constituents.     

Phonetic variability and prosodic structure in mothers

Spontaneous speech acoustics are highly variable. Such variability may be problematic for infants relying on phonological form to solve the segmentation problem. In the present study, acoustic measures of vowel duration and a computer model of speech segmentation were used to evaluate the problem of phonetic variability for a rhythm-based speech segmentation strategy. The specific questions under study were (1) whether or not mothers realized disyllabic vowel duration patterns consistently in spontaneous infant-directed speech, and (2) whether or not these patterns were distinctive enough in the context of an utterance to provide a useful cue for speech segmentation. Data from four English-speaking mothers indicated that the trochaic-like duration pattern may interact with phrase-position and with grammatical category, but when the resulting patterns are consistent, they provide useful segmentation cues for spontaneous infant-directed speech.     

Eye movements and brain electric potentials during reading

The development of theories and computational models of reading requires an understanding of processing constraints, in particular of timelines related to word recognition and oculomotor control. Timelines of word recognition are usually determined with event-related potentials (ERPs) recorded under conditions of serial visual presentation (SVP) of words; timelines of oculomotor control are derived from parameters of eye movements (EMs) during natural reading. We describe two strategies to integrate these approaches. One is to collect ERPs and EMs in separate SVP and natural reading experiments for the same experimental material (but different subjects). The other strategy is to co-register EMs and ERPs during natural reading from the same subjects. Both strategies yield data that allow us to determine how lexical properties influence ERPs (e.g., the N400 component) and EMs (e.g., fixation durations) across neighboring words. We review our recent research on the effects of frequency and predictability of words on both EM and ERP measures with reference to current models of eye-movement control during reading. Results are in support of the proposition that lexical access is distributed across several fixations and across brain-electric potentials measured on neighboring words.