Exploring the Process of Statistical Language Learning

In this thesis, I investigated the process of statistical word segmentation using a combination of behavioural, clinical, and neuroimaging approaches. Prior research has largely focused on the outcome of statistical learning approaches, with little research attention paid to the process of learning. In this body of research, I sought to address this issue. In Chapter 2, I examined how domain-specific and domain-general working memory interference effects on a statistical word segmentation task. I found that when completing a concurrent visuospatial or verbal working memory task, statistical language learning was impaired. Thus, this study provided some evidence that domain-general working memory may support statistical language learning. In Chapter 3, I further investigated how cognitive processes, including language and working memory, are involved in statistical learning across domains. In this study, school-aged children with and without a developmental language disorder (DLD) completed a statistical language learning task and a visual statistical learning task. I found that those with DLD did not differ from typically developing children on either statistical learning task, and that performance across groups was meager for the statistical language learning task, and not above chance levels for the visual statistical learning task. Further, performance on the statistical learning tasks was not associated with other cognitive processes. This raised the possibility that an alternative measurement approach may be better suited to examine statistical learning. I addressed this issue in Chapter 4, where I measured event related potentials (ERPs) using electroencephalography (EEG) during exposure to a structured, unsegmented language. I found that statistical learning performance was related to neural responses to the structured linguistic input, and that ERPs were modulated as a function of language exposure, revealing the dynamic nature of statistical learning. Chapter 5 discusses the relevant findings of this thesis in relation to the current state of affairs in statistical learning research, and presents recommendations for future research in examining the process of statistical learning

Building phonetic categories: an argument for the role of sleep

The current review provides specific predictions for the role of sleep-mediated memory consolidation in the formation of new speech sound representations. Specifically, this discussion will highlight selected literature on the different ideas concerning category representation in speech, followed by a broad overview of memory consolidation and how it relates to human behavior, as relevant to speech/perceptual learning. In combining behavioral and physiological accounts from animal models with insights from the human consolidation literature on auditory skill/word learning, we are in the early stages of understanding how the transfer of experiential information between brain structures during sleep manifests in changes to online perception. Arriving at the conclusion that this process is crucial in perceptual learning and the formation of novel categories, further speculation yields the adjacent claim that the habitual disruption in this process leads to impoverished quality in the representation of speech sounds

A distributional model of semantic context effects in lexical processinga

One of the most robust findings of experimental psycholinguistics is that the context in which a word is presented influences the effort involved in processing that word. We present a novel model of contextual facilitation based on word co-occurrence prob ability distributions, and empirically validate the model through simulation of three representative types of context manipulation: single word priming, multiple-priming and contextual constraint. In our simulations the effects of semantic context are mod eled using general-purpose techniques and representations from multivariate statistics, augmented with simple assumptions reflecting the inherently incremental nature of speech understanding. The contribution of our study is to show that special-purpose m echanisms are not necessary in order to capture the general pattern of the experimental results, and that a range of semantic context effects can be subsumed under the same principled account.›

The ‘nouniness’ of attributive adjectives and ‘verbiness’ of predicative adjectives:Evidence from phonology

This article investigates prototypically attributive versus predicative adjectives in English in terms of the phonological properties that have been associated especially with nouns versus verbs in a substantial body of psycholinguistic research (e.g. Kelly 1992) - often ignored in theoretical linguistic work on word classes. Inspired by Berg's (2000, 2009) 'cross-level harmony constraint', the hypothesis I test is that prototypically attributive adjectives not only align more with nouns than with verbs syntactically, semantically and pragmatically, but also phonologically - and likewise for prototypically predicative adjectives and verbs. I analyse the phonological structure of frequent adjectives from the Corpus of Contemporary American English (COCA), and show that the data do indeed support the hypothesis. Berg's 'cross-level harmony constraint' may thus apply not only to the entire word classes noun, verb and adjective, but also to these two adjectival subclasses. I discuss several theoretical issues that emerge. The facts are most readily accommodated in a usage-based model, such as Radical Construction Grammar (Croft 2001), where these adjectives are seen as forming two distinct but overlapping classes. Drawing also on recent research by Boyd & Goldberg (2011) and Hao (2015), I explore the possible nature and emergence of these classes in some detail

Towards a theory of individual differences in statistical learning

Published 21 November 2016http://rstb.royalsocietypublishing.org/content/372/1711/20160059In recent years, statistical learning (SL) research has seen a growing interest in tracking individual performance in SL tasks, mainly as a predictor of linguistic abilities. We review studies from this line of research and outline three presuppositions underlying the experimental approach they employ: (i) that SL is a unified theoretical construct; (ii) that current SL tasks are interchangeable, and equally valid for assessing SL ability; and (iii) that performance in the standard forced-choice test in the task is a good proxy of SL ability. We argue that these three critical presuppositions are subject to a number of theoretical and empirical issues. First, SL shows patterns of modality- and informational-specificity, suggesting that SL cannot be treated as a unified construct. Second, different SL tasks may tap into separate sub-components of SL that are not necessarily interchangeable. Third, the commonly used forced-choice tests in most SL tasks are subject to inherent limitations and confounds. As a first step, we offer a methodological approach that explicitly spells out a potential set of different SL dimensions, allowing for better transparency in choosing a specific SL task as a predictor of a given linguistic outcome. We then offer possible methodological solutions for better tracking and measuring SL ability. Taken together, these discussions provide a novel theoretical and methodological approach for assessing individual differences in SL, with clear testable predictions. This article is part of the themed issue ‘New frontiers for statistical learning in the cognitive sciences’.This article was supported by the Israel Science Foundation (Grant No. 217/14, awarded to R.F.), by the National Institute of Child Health and Human Development (Grant Nos. RO1 HD 067364, awarded to Ken Pugh and R.F., and PO1-HD 01994, awarded to Haskins Laboratories), and by the ERC (project 692502, awarded to R.F.). L.B. is a research fellow of the Fyssen Foundation

Semantic Memory

How is it that we know what a dog and a tree are, or, for that matter, what knowledge is? Our semantic memory consists of knowledge about the world, including concepts, facts and beliefs. This knowledge is essential for recognizing entities and objects, and for making inferences and predictions about the world. In essence, our semantic knowledge determines how we understand and interact with the world around us. In this chapter, we examine semantic memory from cognitive, sensorimotor, cognitive neuroscientific, and computational perspectives. We consider the cognitive and neural processes (and biases) that allow people to learn and represent concepts, and discuss how and where in the brain sensory and motor information may be integrated to allow for the perception of a coherent “concept”. We suggest that our understanding of semantic memory can be enriched by considering how semantic knowledge develops across the lifespan within individuals

Predictive processing and developmental language disorder

Purpose: Research in the cognitive and neural sciences has situated predictive processing – the anticipation of upcoming percepts – as a dominant function of the brain. The purpose of this article is to argue that prediction should feature more prominently in explanatory accounts of sentence processing and comprehension deficits in developmental language disorder (DLD). Method: We evaluate behavioural and neurophysiological data relevant to the theme of prediction in early typical and atypical language acquisition and processing. Results: Poor syntactic awareness – attributable in part to an underlying statistical learning deficit – is likely to impede syntax-based predictive processing in children with DLD, conferring deficits in spoken sentence comprehension. Furthermore, there may be a feedback cycle in which poor syntactic awareness impedes children’s ability to anticipate upcoming percepts, and this in turn makes children unable to improve their syntactic awareness on the basis of prediction error signals. Conclusion: This article offers a re-focusing of theory on sentence processing and comprehension deficits in DLD, from a difficulty in processing and integrating perceived syntactic features, to a difficulty in anticipating what is coming next

Frequency-based neural discrimination in fast periodic visual stimulation

Humans capitalize on statistical cues to discriminate fundamental units of information within complex streams of sensory input. We sought neural evidence for this phenomenon by combining fast periodic visual stimulation (FPVS) and EEG recordings. Skilled readers were exposed to sequences of linguistic items with decreasing familiarity, presented at a fast rate and periodically interleaved with oddballs. Crucially, each sequence comprised stimuli of the same category, and the only distinction between base and oddball items was the frequency of occurrence of individual tokens within a stream. Frequency-domain analyses revealed robust neural responses at the oddball presentation rate in all conditions, reflecting the discrimination between two locally-emerged groups of items purely informed by token frequency. Results provide evidence for a fundamental frequency-tuned mechanism that operates under high temporal constraints and could underpin category bootstrapping. Concurrently, they showcase the potential of FPVS for providing a direct neural measure of implicit statistical learning

Language learning in infancy

Although immensely complex, speech is also a very efficient means of communication between humans. Understanding how we acquire the skills necessary for perceiving and producing speech remains an intriguing goal for research. However, while learning is likely to begin as soon as we start hearing speech, the tools for studying the language acquisition strategies in the earliest stages of development remain scarce. One prospective strategy is statistical learning. In order to investigate its role in language development, we designed a new research method. The method was tested in adults using magnetoencephalography (MEG) as a measure of cortical activity. Neonatal brain activity was measured with electroencephalography (EEG). Additionally, we developed a method for assessing the integration of seen and heard syllables in the developing brain as well as a method for assessing the role of visual speech when learning phoneme categories. The MEG study showed that adults learn statistical properties of speech during passive listening of syllables. The amplitude of the N400m component of the event-related magnetic fields (ERFs) reflected the location of syllables within pseudowords. The amplitude was also enhanced for syllables in a statistically unexpected position. The results suggest a role for the N400m component in statistical learning studies in adults. Using the same research design with sleeping newborn infants, the auditory event-related potentials (ERPs) measured with EEG reflected the location of syllables within pseudowords. The results were successfully replicated in another group of infants. The results show that even newborn infants have a powerful mechanism for automatic extraction of statistical characteristics from speech. We also found that 5-month-old infants integrate some auditory and visual syllables into a fused percept, whereas other syllable combinations are not fully integrated. Auditory syllables were paired with visual syllables possessing a different phonetic identity, and the ERPs for these artificial syllable combinations were compared with the ERPs for normal syllables. For congruent auditory-visual syllable combinations, the ERPs did not differ from those for normal syllables. However, for incongruent auditory-visual syllable combinations, we observed a mismatch response in the ERPs. The results show an early ability to perceive speech cross-modally. Finally, we exposed two groups of 6-month-old infants to artificially created auditory syllables located between two stereotypical English syllables in the formant space. The auditory syllables followed, equally for both groups, a unimodal statistical distribution, suggestive of a single phoneme category. The visual syllables combined with the auditory syllables, however, were different for the two groups, one group receiving visual stimuli suggestive of two separate phoneme categories, the other receiving visual stimuli suggestive of only one phoneme category. After a short exposure, we observed different learning outcomes for the two groups of infants. The results thus show that visual speech can influence learning of phoneme categories. Altogether, the results demonstrate that complex language learning skills exist from birth. They also suggest a role for the visual component of speech in the learning of phoneme categories.Puhe on monimuotoinen signaali, joka välittää ihmistenvälistä kommunikaatiota erityisen tehokkaasti. On osin vielä hämärän peitossa, miten opimme puhumaan ja havaitsemaan puhetta syntymän jälkeen. Oppiminen alkanee heti, kun alamme kuulla puhetta. Puheen sisältämät lukuisat tilastolliset säännönmukaisuudet saattavat auttaa oppimista. Niiden hyödyntämistä kutsutaan tilastolliseksi oppimiseksi. Tilastollista oppimista ajatellaan kielenoppimisessa voitavan käyttää jatkuvan puheen jakamiseksi erillisiksi sanoiksi. Tässä tutkimuksessa kehitettiin uusi aivomittauksiin perustuva tutkimusmenetelmä tilastollisen kielenoppimisen mittaamiseksi. Menetelmää testattiin aikuisilla mittaamalla aivokuoriaktivaatiota magnetoenkefalografiaa käyttäen. Tulokset osoittivat, että aikuiset oppivat tilastollisia ominaisuuksia tavuvirrasta silloinkin, kun he eivät kiinnitä siihen tietoisesti huomiota. Tilastollista oppimista pystyttiin mittaamaan aivojen magneettisissa herätevasteissa näkyvän N400m-vasteen yhteydessä. Samaa koeasetelmaa käytettiin mittamaan tilastollisen kielenoppimisen kykyjä vastasyntyneiltä käyttäen elektroenkefalografiaa aivotoiminnan mittarina. Tulokset osoittivat, että vastasyntyneet oppivat tilastollisia riippuvuuksia tavujen välillä unen aikana kuulemastaan tavuvirrasta. Tutkimustulos toistui myös toisella ryhmällä vastasyntyneitä. Jo vastasyntyneillä on siis hyvä puheen tilastollisten ominaisuuksien oppimiskyky. Tehokkaassa puheenhavaitsemisessa olennaisena pidetään kykyä yhdistää eli integroida kuultu puhe ja nähty artikulaatio yhdeksi havainnoksi. Ajatellaan, että aikuisilla aivot käsittelevät integroidun puheen tehokkaammin kuin erilliset kuulo- ja näköhavainnot. Kehitimme koeasetelman kuullun ja nähdyn puheen integroinnin mittaamiseksi viiden kuukauden ikäisillä vauvoilla. Tulokset osoittivat, että tässä kehitysvaiheessa vauvat muodostavat yhdistyneen havainnon tietyistä kuulluista ja nähdyistä tavuista, kun taas toisia tavuyhdistelmiä ei integroida. Koska integrointi ei onnistu tilanteessa, jossa muodostuva havainto ei ole äidinkielen sääntöjen mukainen, tulokset myös viittaavat siihen, että viiden kuukauden iässä vauvat ovat jo omaksuneet tietoa äidinkielen tyypillisistä rakenteista. Lopuksi arvioitiin myös sitä, millainen rooli nähdyllä puheella saattaisi olla kielenoppimisessa. Kaksi ryhmää kuuden kuukauden ikäisiä vauvoja osallistui kokeeseen. Vauvoille näytettiin ruudulta puhetta, jossa videoon tavallisesta artikulaatiosta oli liitetty keinotekoisesti muokattuja tavuääniä. Osalle vauvoista nähty puhe sisälsi vihjeen kahdesta erilaisesta tavuryhmästä, kun taas toiselle ryhmälle nähty puhe pysyi koko ajan samanlaisena. Kuultu puhe oli kaikille vauvoille täysin samanlaista. Lyhyen katselu- ja kuunteluajan jälkeen vauvojen havaintoa kyseisistä tavuäänistä testattiin. Eri ryhmillä havaittiin erilaiset oppimistulokset, joka viittaa siihen, että nähdyillä artikulaatioilla oli vaikutusta oppimiseen. Nähty puhe siis voi vaikuttaa puheäänten oppimiseen tässä kehitysvaiheessa. Kokonaisuudessaan tässä väitöskirjassa esitetyt tulokset korostavat varhaisimpien vaiheiden merkitystä kielenoppimisessa. Pystymme oppimaan puheen ominaisuuksia monipuolisesti heti syntymästä lähtien. Tulokset myös viittaavat siihen, että nähdyllä puheella saattaa olla tärkeä rooli puheäänien oppimisessa ensimmäisen vuoden aikana