Publications

Abstract

Anaphora, a ubiquitous feature of natural language, poses a particular challenge to young children as they first learn language due to its referential ambiguity. In spite of this, parents and caregivers use anaphora frequently in child-directed speech, potentially presenting a risk to effective communication if children do not yet have the linguistic capabilities of resolving anaphora successfully. Through an eye-tracking study in a naturalistic free-play context, we examine the strategies that parents employ to calibrate their use of anaphora to their child's linguistic development level. We show that, in this way, parents are able to intuitively scaffold the complexity of their speech such that greater referential ambiguity does not hurt overall communication success.

Abstract

With the aim to clarify the definition of humans as “linguistic animals”, in the present paper I functionally distinguish three types of language competences: i) language as a general biological tool for communication, ii) “perceptual syntax”, iii) propositional language. Following this terminological distinction, I review pivotal findings on animals' communication systems, which constitute useful evidence for the investigation of the nature of three core components of humans' faculty of language: semantics, syntax, and theory of mind. In fact, despite the capacity to process and share utterances with an open-ended structure is uniquely human, some isolated components of our linguistic competence are in common with nonhuman animals. Therefore, as I argue in the present paper, the investigation of animals' communicative competence provide crucial insights into the range of cognitive constraints underlying humans' ability of language, enabling at the same time the analysis of its phylogenetic path as well as of the selective pressures that have led to its emergence.

Abstract

The aim of this study is to investigate the word-learning phenomenon utilizing a new model that integrates three processes: a) extracting a word out of a continuous sounds sequence, b) inducing referential meanings, c) mapping a word onto its intended referent, with the possibility to extend the acquired word over a potentially infinite sets of objects of the same semantic category, and over not-previously-heard utterances. Previous work has examined the role of statistical learning and/or of prosody in each of these processes separately. In order to examine the multilayered word-learning task, we integrate these two strands of investigation into a single approach. We have conducted the study on adults and included six different experimental conditions, each including specific perceptual manipulations of the signal. In condition 1, the only cue to word-meaning mapping was the co-occurrence between words and referents (“statistical cue”). This cue was present in all the conditions. In condition 2, we added infant-directed-speech (IDS) typical pitch enhancement as a marker of the target word and of the statistical cue. In condition 3 we placed IDS typical pitch enhancement on random words of the utterances, i.e. inconsistently matching the statistical cue. In conditions 4, 5 and 6 we manipulated respectively duration, a non-prosodic acoustic cue and a visual cue as markers of the target word and of the statistical cue. Systematic comparisons between learning performance in condition 1 with the other conditions revealed that the word-learning process is facilitated only when pitch prominence consistently marks the target word and the statistical cue…

Abstract

This chapter highlights the research in isolating genetic factors underlying specific language impairment (SLI), or developmental dysphasia, which exploits newly developed genotyping technology, novel statistical methodology, and DNA sequence data generated by the Human Genome Project. The author begins with an overview of results from family, twin, and adoption studies supporting genetic involvement and then goes on to outline progress in a number of genetic mapping efforts that have been recently completed or are currently under way. It has been possible for genetic researchers to pinpoint the specific mutation responsible for some speech and language disorders, providing an example of how the availability of human genomic sequence data can greatly accelerate the pace of disease gene discovery. Finally, the author discusses future prospects on how molecular genetics may offer new insight into the etiology underlying speech and language disorders, leading to improvements in diagnosis and treatment.

Abstract

Relative clauses are a syntactic device to create complex sentences and they make language structurally productive. Despite a considerable number of experimental studies, it is still largely unclear how children learn relative clauses and how these are processed in the language system. Researchers at the MPI for Psycholinguistics used a computational learning model to gain novel insights into these issues. The model explains the differential development of relative clauses in English as well as cross-linguistic differences

Abstract

The Cha’palaa language of Ecuador (Barbacoan) features verbal morphology for marking knowledge-based categories that, in usage, show a variant of the cross-linguistically recurrent pattern of ‘egophoric distribution': specific forms associate with speakers in contrast to others in statements and with addressees in contrast to others in questions. These are not person markers, but rather are used by speakers to portray their involvement in states of affairs as active, agentive participants (ego) versus other types of involvement (non-ego). They interact with person and argument structure, but through pragmatic ‘person sensitivities’ rather than through grammatical agreement. Not only does this pattern appear in verbal morphology, it also can be observed in alternations of predicate construction types and case alignment, helping to show how egophoric marking is a pervasive element of Cha'palaa's linguistic system. This chapter gives a first account of egophoricity in Cha’palaa, beginning with a discussion of person sensitivity, egophoric distribution, and issues of flexibility of marking with respect to degree of volition or control. It then focuses on a set of intransitive experiencer (or ‘endopathic') predicates that refer to internal states which mark egophoric values for the undergoer role, not the actor role, showing ‘quirky’ accusative marking instead of nominative case. It concludes with a summary of how egophoricity in Cha'palaa interacts with issues of argument structure in comparison to a language with person agreement, here represented by examples from Cha’palaa’s neighbor Ecuadorian Highland Quechua.

Abstract

This chapter connects the grammar of the first person collective pronoun in the Cha’palaa language of Ecuador with its use in interaction for collective reference and social category membership attribution, addressing the problem posed by the fact that non-singular pronouns do not have distributional semantics (“speakers”) but are rather associational (“speaker and relevant associates”). It advocates a cross-disciplinary approach that jointly considers elements of linguistic form, situated usages of those forms in instances of interaction, and the broader ethnographic context of those instances. Focusing on large-scale and relatively stable categories such as racial and ethnic groups, it argues that looking at how speakers categorize themselves and others in the speech situation by using pronouns provides empirical data on the status of macro-social categories for members of a society

Abstract

Structural imaging based on computerized tomography (CT) and magnetic resonance imaging (MRI) has progressively replaced traditional post‐mortem studies in the process of identifying the neuroanatomical basis of language. In the clinical setting, the information provided by structural imaging has been used to confirm the exact diagnosis and formulate an individualized treatment plan. In the research arena, neuroimaging has permitted to understand neuroanatomy at the individual and group level. The possibility to obtain quantitative measures of lesions has improved correlation analyses between severity of symptoms, lesion load, and lesion location. More recently, the development of structural imaging based on diffusion MRI has provided valid solutions to two major limitations of more conventional imaging. In stroke patients, diffusion can visualize early changes due to a stroke that are otherwise not detectable with more conventional structural imaging, with important implications for the clinical management of acute stroke patients. Beyond the sensitivity to early changes, diffusion imaging tractography presents the possibility of visualizing the trajectories of individual white matter pathways connecting distant regions. A pathway analysis based on tractography is offering a new perspective in neurolinguistics. First, it permits to formulate new anatomical models of language function in the healthy brain and allows to directly test these models in the human population without any reliance on animal models. Second, by defining the exact location of the damage to specific white matter connections we can understand the contribution of different mechanisms to the emergence of language deficits (e.g., cortical versus disconnection mechanisms). Finally, a better understanding of the anatomical variability of different language networks is helping to identify new anatomical predictors of language recovery. In this chapter we will focus on the principles of structural MRI and, in particular, diffusion imaging and tractography and present examples of how these methods have informed our understanding of variance in language performances in the healthy brain and language deficits in patient populations.

Abstract

Turn on your affective system by tweaking your face muscles - or getting an eyeful of someone else doing the same.

Abstract

Find the fire that's cooking your memory systems.

Abstract

Emotions are powerful on the inside but often displayed in subtle ways on the outside. Are these displays culturally dependent or universal?

Abstract

Reading is an audiovisual process that requires the learning of systematic links between graphemes and phonemes. It is thus possible that reading impairments reflect an audiovisual processing deficit. In this study, we compared audiovisual processing in adults with developmental dyslexia and adults without reading difficulties. We focused on differences in cross-modal temporal sensitivity both for speech and for non-speech events. When compared to adults without reading difficulties, adults with developmental dyslexia presented a wider temporal window in which unsynchronized speech events were perceived as synchronized. No differences were found between groups for the non-speech events. These results suggests a deficit in dyslexia in the perception of cross-modal temporal synchrony for speech events.

Abstract

Several sources of information are used in choosing the intended referent of an ambiguous pronoun. The two sources considered in this paper are foregrounding and context. The first refers to the accessibility of discourse entities. An entity that is foregrounded is more likely to become the pronoun’s referent than an entity that is not. Context information affects pronoun resolution when world knowledge is needed to find the referent. The model presented here simulates how world knowledge invoked by context, together with foregrounding, influences pronoun resolution. It was developed as an extension to the Distributed Situation Space (DSS) model of knowledge-based inferencing in story comprehension (Frank, Koppen, Noordman, & Vonk, 2003), which shall be introduced first.

Abstract

Language acquisition is complex. However, one thing that has been suggested to help learning is the way that information is distributed throughout language; co-occurrences among particular items (e.g., syllables and words) have been shown to help learners discover the words that a language contains and figure out how those words are used. Humans’ ability to draw on this information—“statistical learning”—has been demonstrated across a broad range of studies. However, evidence from non-WEIRD (Western, Educated, Industrialized, Rich, and Democratic) societies is critically lacking, which limits theorizing on the universality of this skill. We extended work on statistical language learning to a new, non-WEIRD linguistic population: speakers of Yélî Dnye, who live on a remote island off mainland Papua New Guinea (Rossel Island). We performed a replication of an existing statistical learning study, training adults on an artificial language with statistically defined words, then examining what they had learnt using a two-alternative forced-choice test. Crucially, we implemented several key amendments to the original study to ensure the replication was suitable for remote field-site testing with speakers of Yélî Dnye. We made critical changes to the stimuli and materials (to test speakers of Yélî Dnye, rather than English), the instructions (we re-worked these significantly, and added practice tasks to optimize participants’ understanding), and the study format (shifting from a lab-based to a portable tablet-based setup). We discuss the requirement for acute sensitivity to linguistic, cultural, and environmental factors when adapting studies to test new populations.

Abstract

This project is part of a collaborative project with the research group “Reciprocals across languages” led by Nick Evans. One goal of this project is to develop a typology of reciprocals. This questionnaire is designed to help field workers get an overview over the type of markers used in the expression of reciprocity in the language studied.

Abstract

Graph neural networks (GNNs) have emerged as the standard method for numerous tasks on graph-structured data such as node classification. However, real-world graphs are often evolving over time and even new classes may arise. We model these challenges as an instance of lifelong learning, in which a learner faces a sequence of tasks and may take over knowledge acquired in past tasks. Such knowledge may be stored explicitly as historic data or implicitly within model parameters. In this work, we systematically analyze the influence of implicit and explicit knowledge. Therefore, we present an incremental training method for lifelong learning on graphs and introduce a new measure based on k-neighborhood time differences to address variances in the historic data. We apply our training method to five representative GNN architectures and evaluate them on three new lifelong node classification datasets. Our results show that no more than 50% of the GNN's receptive field is necessary to retain at least 95% accuracy compared to training over the complete history of the graph data. Furthermore, our experiments confirm that implicit knowledge becomes more important when fewer explicit knowledge is available.

Abstract

We analyze the problem of response suggestion in a closed domain along a real-world scenario of a digital library. We present a text-processing pipeline to generate question-answer pairs from chat transcripts. On this limited amount of training data, we compare retrieval-based, conditioned-generation, and dedicated representation learning approaches for response suggestion. Our results show that retrieval-based methods that strive to find similar, known contexts are preferable over parametric approaches from the conditioned-generation family, when the training data is limited. We, however, identify a specific representation learning approach that is competitive to the retrieval-based approaches despite the training data limitation.

Abstract

COVID-19 research datasets are crucial for analyzing research dynamics. Most collections of COVID-19 research items do not to include cited works and do not have annotations
from a controlled vocabulary. Starting with ZB MED KE data on COVID-19, which comprises CORD-19, we assemble a new dataset that includes cited work and MeSH annotations for all records. Furthermore, we conduct experiments on the analysis of research dynamics, in which we investigate predicting links in a co-annotation graph created on the basis of the new dataset. Surprisingly, we find that simple heuristic methods are better at
predicting future links than more sophisticated approaches such as graph neural networks.

Abstract

We present multi-modal adversarial autoencoders for recommendation and evaluate them on two different tasks: citation recommendation and subject label recommendation. We analyze the effects of adversarial regularization, sparsity, and different input modalities. By conducting 408 experiments, we show that adversarial regularization consistently improves the performance of autoencoders for recommendation. We demonstrate, however, that the two tasks differ in the semantics of item co-occurrence in the sense that item co-occurrence resembles relatedness in case of citations, yet implies diversity in case of subject labels. Our results reveal that supplying the partial item set as input is only helpful, when item co-occurrence resembles relatedness. When facing a new recommendation task it is therefore crucial to consider the semantics of item co-occurrence for the choice of an appropriate model.

Abstract

Researchers have long avoided neurophysiological experiments of overt speech production due to the suspicion that artifacts caused by muscle activity may lead to a bad signal-to-noise ratio in the measurements. However, the need to actually produce speech may influence earlier processing and qualitatively change speech production processes and what we can infer from neurophysiological measures thereof. Recently, however, overt speech has been successfully investigated using EEG, MEG, and fMRI. The aim of this Research Topic is to draw together recent research on the neurophysiological basis of language production, with the aim of developing and extending theoretical accounts of the language production process. In this Research Topic of Frontiers in Language Sciences, we invite both experimental and review papers, as well as those about the latest methods in acquisition and analysis of overt language production data. All aspects of language production are welcome: i.e., from conceptualization to articulation during native as well as multilingual language production. Focus should be placed on using the neurophysiological data to inform questions about the processing stages of language production. In addition, emphasis should be placed on the extent to which the identified components of the electrophysiological signal (e.g., ERP/ERF, neuronal oscillations, etc.), brain areas or networks are related to language comprehension and other cognitive domains. By bringing together electrophysiological and neuroimaging evidence on language production mechanisms, a more complete picture of the locus of language production processes and their temporal and neurophysiological signatures will emerge.

Abstract

We present a solution to the problem of online speaker/signer diarization - the task of determining "who spoke/signed when?". Our solution is based on the idea that gestural activity (hands and body movement) is highly correlated with uttering activity. This correlation is necessarily true for sign languages and mostly true for spoken languages. The novel part of our solution is the use of motion history images (MHI) as a likelihood measure for probabilistically detecting uttering activities. MHI is an efficient representation of where and how motion occurred for a fixed period of time. We conducted experiments on 4.9 hours of a publicly available dataset (the AMI meeting data) and 1.4 hours of sign language dataset (Kata Kolok data). The best performance obtained is 15.70% for sign language and 31.90% for spoken language (measurements are in DER). These results show that our solution is applicable in real-world applications like video conferences.

Abstract

We demonstrate how the problem of speaker diarization can be solved using both gesture and speaker parametric models. The novelty of our solution is that we approach the speaker diarization problem as a speaker recognition problem after learning speaker models from speech samples corresponding to gestures (the occurrence of gestures indicates the presence of speech and the location of gestures indicates the identity of the speaker). This new approach offers many advantages: comparable state-of-the-art performance, faster computation and more adaptability. In our implementation, parametric models are used to model speakers' voice and their gestures: more specifically, Gaussian mixture models are used to model the voice characteristics of each person and all persons, and gamma distributions are used to model gestural activity based on features extracted from Motion History Images. Tests on 4.24 hours of the AMI meeting data show that our solution makes DER score improvements of 19% on speech-only segments and 4% on all segments including silence (the comparison is with the AMI system).

Abstract

Prior research on language identification focused primarily on text and speech. In this paper, we focus on the visual modality and present a method for identifying sign languages solely from short video samples. The method is trained on unlabelled video data (unsupervised feature learning) and using these features, it is trained to discriminate between six sign languages (supervised learning). We ran experiments on video samples involving 30 signers (running for a total of 6 hours). Using leave-one-signer-out cross-validation, our evaluation on short video samples shows an average best accuracy of 84%. Given that sign languages are under-resourced, unsupervised feature learning techniques are the right tools and our results indicate that this is realistic for sign language identification.

Abstract

What does semantic similarity between two concepts mean? How could we measure it? The way in which semantic similarity is calculated might differ depending on the theoretical notion of semantic representation. In an eye-tracking reading experiment, we investigated whether two widely used semantic similarity measures (based on featural or distributional representations) have distinctive effects on sentence reading times. In other words, we explored whether these measures of semantic similarity differ qualitatively. In addition, we examined whether visually perceived spatial distance interacts with either or both of these measures. Our results showed that the effect of featural and distributional representations on reading times can differ both in direction and in its time course. Moreover, both featural and distributional information interacted with spatial distance, yet in different sentence regions and reading measures. We conclude that featural and distributional representations are distinct components of semantic representation.

Abstract

Recent evidence from eye tracking during reading showed that non-referential spatial distance presented in a visual context can modulate semantic interpretation of similarity relations rapidly and incrementally. In two eye-tracking reading experiments we extended these findings in two important ways; first, we examined whether other semantic domains (social relations) could also be rapidly influenced by spatial distance during sentence comprehension. Second, we aimed to further specify how abstract language is co-indexed with spatial information by varying the syntactic structure of sentences between experiments. Spatial distance rapidly modulated reading times as a function of the social relation expressed by a sentence. Moreover, our findings suggest that abstract language can be co-indexed as soon as critical information becomes available for the reader.

Abstract

Trumai, a genetically isolated language spoken in Brazil (Xingu reserve), is an example of an endangered language. Although the Trumai population consists of more than 100 individuals, only 51 people speak the language. The oral traditions are progressively dying. Given the current scenario, the documentation of this language and its cultural aspects is of great importance. In the framework of the DoBeS program (Documentation of Endangered Languages), the project "Documentation of Trumai" has selected and organized a collection of Trumai texts, with a multi-media representation of the corpus. Several kinds of information and data types are being included in the archive of the language: texts with audio and video recordings; written texts from educational materials; drawings; photos; songs; annotations in different formats; lexicon; field notes; results from scientific studies of the language (sound system, sketch grammar, comparative studies with other Xinguan languages), etc. All materials are integrated into the IMDI-Browser, a specialized tool for presenting and searching for linguistic data. This paper explores the processing phases and the results of the Trumai project taking into consideration the issue of how to combine the needs and wishes of field linguistics (content and research aspects) and the needs of archiving (structure and workflow aspects) in a well-organized corpus.

Abstract

Gestures are visuospatial events, meaning carriers, and social interactional phenomena. As such they constitute a particularly favourable area for investigating visual attention in a complex everyday situation under conditions of competitive processing. This chapter discusses visual attention to spontaneous gestures in human face-to-face interaction as explored with eye-tracking. Some basic fixation patterns are described, live and video-based settings are compared, and preliminary results on the relationship between fixations and information processing are outlined.

Abstract

This paper discusses how the gestural modality can contribute to our understanding of anaphoric linkage in learner varieties, focusing on gestural anaphoric linkage marking the introduction, maintenance, and shift of reference in story retellings by learners of French and Swedish. The comparison of gestural anaphoric linkage in native and non-native varieties reveals what appears to be a particular learner variety of gestural cohesion, which closely reflects the characteristics of anaphoric linkage in learners' speech. Specifically, particular forms co-occur with anaphoric gestures depending on the information organisation in discourse. The typical nominal over-marking of maintained referents or topic elements in speech is mirrored by gestural (over-)marking of the same items. The paper discusses two ways in which this finding may further the understanding of anaphoric over-explicitness of learner varieties. An addressee-based communicative perspective on anaphoric linkage highlights how over-marking in gesture and speech may be related to issues of hyper-clarity and ambiguity. An alternative speaker-based perspective is also explored in which anaphoric over-marking is seen as related to L2 speech planning.

Abstract

A prototypical lexicon tool was implemented which was intended to allow researchers to collaboratively create lexicons of endangered languages. Increasingly often researchers documenting or analyzing a language work at different locations. Lexicons that evolve through continuous interaction between the collaborators can only be efficiently produced when it can be accessed and manipulated via the Internet. The SHAWEL tool was developed to address these needs; it makes use of a thin Java client and a central database solution.

Abstract

Whitesands is an Oceanic language of the southern Vanuatu subgroup. Like the related languages of southern Vanuatu, Whitesands has developed a clause-linkage system which monitors referent continuity on new clauses – typically contrasting with the previous clause. In this chapter I address how the construction interacts with topic continuity in discourse. I outline the morphosyntactic form of this anaphoric co-reference device. From a functionalist perspective, I show how the system is used in natural discourse and discuss its restrictions with respect to relative and complement clauses. I conclude with a discussion on its interactions with theoretical notions of information structure – in particular the nature of presupposed versus asserted clauses, information back- and foregrounding and how these affect the use of the switch-reference system

Abstract

We present a quantitative model of word order and movement constraints that enables a simple and uniform treatment of a seemingly heterogeneous collection of linear order phenomena in English, Dutch and German complement constructions (Wh-extraction, clause union, extraposition, verb clustering, particle movement, etc.). Underlying the scheme are central assumptions of the psycholinguistically motivated Performance Grammar (PG). Here we describe this formalism in declarative terms based on typed feature unification. PG allows a homogenous treatment of both the within- and between-language variations of the ordering phenomena under discussion, which reduce to different settings of a small number of quantitative parameters.

Abstract

Children with developmental language disorder (DLD) regularly use the base form of verbs (e.g., dance) instead of inflected forms (e.g., danced). We propose an account of this behavior in which children with DLD have difficulty processing novel inflected verbs in their input. This leads the inflected form to face stronger competition from alternatives. Competition is resolved by the production of a more accessible alternative with high semantic overlap with the inflected form: in English, the bare form. We test our account computationally by training a nonparametric Bayesian model that infers the productivity of the inflectional suffix (-ed). We systematically vary the number of novel types of inflected verbs in the input to simulate the input as processed by children with and without DLD. Modeling results are consistent with our hypothesis, suggesting that children’s inconsistent use of inflectional morphemes could stem from inferences they make on the basis of impoverished data.

Abstract

This paper reports on an on-going project designed to collect comparable corpus data on child language and child-directed language in under-researched languages. Despite a long history of cross-linguistic research, there is a severe empirical bias within language acquisition research: Data is available for less than 2% of the world's languages, heavily skewed towards the larger and better-described languages. As a result, theories of language development tend to be grounded in a non-representative sample, and we know little about the acquisition of typologically-diverse languages from different families, regions, or sociocultural contexts. It is very likely that the reasons are to be found in the forbidding methodological challenges of constructing child language corpora under fieldwork conditions with their strict requirements on participant selection, sampling intervals, and amounts of data. There is thus an urgent need for proposals that facilitate and encourage language acquisition research across a wide variety of languages. Adopting a language documentation perspective, we illustrate an approach that combines the construction of manageable corpora of natural interaction with and between children with a sketch description of the corpus data – resulting in a set of comparable corpora and comparable sketches that form the basis for cross-linguistic comparisons.

Abstract

The use of virtual reality (VR) as a methodological tool is
becoming increasingly popular in behavioural research due
to its seemingly limitless possibilities. This new method has
not been used frequently in the field of psycholinguistics,
however, possibly due to the assumption that humancomputer
interaction does not accurately reflect human-human
interaction. In the current study we compare participants’
language behaviour in a syntactic priming task with human
versus avatar partners. Our study shows comparable priming
effects between human and avatar partners (Human: 12.3%;
Avatar: 12.6% for passive sentences) suggesting that VR is a
valid platform for conducting language research and studying
dialogue interactions.

Abstract

Using the visual-word paradigm, the present study investigated the effects of word onset and offset masking on the time course of non-native spoken-word recognition in the presence of background noise. In two experiments, Dutch non-native listeners heard English target words, preceded by carrier sentences that were noise-free (Experiment 1) or contained intermittent noise (Experiment 2). Target words were either onset- or offset-masked or not masked at all. Results showed that onset masking delayed target word recognition more than offset masking did, suggesting that – similar to natives – non-native listeners strongly rely on word onset information during word recognition in noise.

Abstract

Conversation Analysis (CA) is an inductive, micro-analytic, and predominantly qualitative
method for studying human social interactions. This chapter describes and illustrates the basic
methods of CA. We first situate the method by describing its sociological foundations, key areas
of analysis, and particular approach in using naturally occurring data. The bulk of the chapter is
devoted to practical explanations of the typical conversation analytic process for collecting data
and producing an analysis. We analyze a candidate interactional practice – the assessmentimplicative
interrogative – using real data extracts as a demonstration of the method, explicitly
laying out the relevant questions and considerations for every stage of an analysis. The chapter
concludes with some discussion of quantitative approaches to conversational interaction, and
links between CA and psycholinguistic concerns

Abstract

In this paper, we show how acoustic variance within lexical tones in disyllabic Mandarin Chinese pseudowords affects discrimination abilities in both native and non-native speakers of Mandarin Chinese. Within-category acoustic variance did not hinder native speakers in discriminating between lexical tones, whereas it precludes Dutch native speakers from reaching native level performance. Furthermore, the influence of acoustic variance was not uniform but asymmetric, dependent on the presentation order of the lexical tones to be discriminated. An exploratory analysis using an active adaptive oddball paradigm was used to quantify the extent of the perceptual asymmetry. We discuss two possible mechanisms underlying this asymmetry and propose possible paradigms to investigate these mechanisms

Abstract

What makes some words harder to learn than others in a second language? Although some robust factors have been identified based on small scale experimental studies, many relevant factors are difficult to study in such experiments due to the amount of data necessary to test them. Here, we investigate what factors affect the ease of learning of a word in a second language using a large data set of users learning English as a second language through the Duolingo mobile app. In a regression analysis, we test and confirm the well-studied effect of cognate status on word learning accuracy. Furthermore, we find significant effects for both cross-linguistic semantic alignment and English semantic density, two novel predictors derived from large scale distributional models of lexical semantics. Finally, we provide data on several other psycholinguistically plausible word level predictors. We conclude with a discussion of the limits, benefits and future research potential of using big data for investigating second language learning.

Abstract

This paper presents a meta-analysis of hemodynamic studies on passive auditory language processing. We assess the overlap of hemodynamic activation areas and activation maxima reported in experiments involving the presentation of sentences, words, pseudowords, or sublexical or non-linguistic auditory stimuli. Areas that have been reliably replicated are identified. The results of the meta-analysis are compared to electrophysiological, magnetencephalic (MEG), and clinical findings. It is concluded that auditory language input is processed in a left posterior frontal and bilateral temporal cortical network. Within this network, no processing leve l is related to a single cortical area. The temporal lobes seem to differ with respect to their involvement in post-lexical processing, in that the left temporal lobe has greater involvement than the right, and also in the degree of anatomical specialization for phonological, lexical, and sentence -level processing, with greater overlap on the right contrasting with a higher degree of differentiation on the left.

Abstract

This chapter deals with the question of whether there is one syntactic system that is shared by language production and comprehension or whether there are two separate systems. It first discusses arguments in favor of one or the other option and then presents the current evidence on the brain structures involved in sentence processing. The results of meta-analyses of numerous neuroimaging studies suggest that there is one system consisting of functionally distinct cortical regions: the dorsal part of Broca’s area subserving compositional syntactic processing; the ventral part of Broca’s area subserving compositional semantic processing; and the left posterior temporal cortex (Wernicke’s area) subserving the retrieval of lexical syntactic and semantic information. Sentence production, the comprehension of simple and complex sentences, and the parsing of sentences containing grammatical violations differ with respect to the recruitment of these functional components.

Abstract

A common assumption in the cognitive sciences is that artificial and natural language learning rely on shared mechanisms. However, attempts to bridge the two have yielded ambiguous results. We suggest that an empirical disconnect between the computations employed during learning and the methods employed at test may explain these mixed results. Further, we propose statistically-based chunking as a potential computational link between artificial and natural language learning. We compare the acquisition of non-adjacent dependencies to that of natural language structure using two types of tasks: reflection-based 2AFC measures, and processing-based recall measures, the latter being more computationally analogous to the processes used during language acquisition. Our results demonstrate that task-type significantly influences the correlations observed between artificial and natural language acquisition, with reflection-based and processing-based measures correlating within – but not across – task-type. These findings have fundamental implications for artificial-to-natural language comparisons, both methodologically and theoretically.

Abstract

Computer models of cultural evolution have shown language properties emerging on interacting agents with a brain that lacks dedicated, nativist language modules. Notably, models using Bayesian agents provide a precise specification of (extra-)liguististic factors (e.g., genetic) that shape language through iterated learning (biases on language), and demonstrate that weak biases get expressed more strongly over time (bias amplification). Other models attempt to lessen assumption on agents’ innate predispositions even more, and emphasize self-organization within agents, highlighting glossogenesis (the development of language from a nonlinguistic state). Ultimately however, one also has to recognize that biology and culture are strongly interacting, forming a coevolving system. As such, computer models show that agents might (biologically) evolve to a state predisposed to language adaptability, where (culturally) stable language features might get assimilated into the genome via Baldwinian niche construction. In summary, while many questions about language evolution remain unanswered, it is clear that it is not to be completely understood from a purely biological, cognitivist perspective. Language should be regarded as (partially) emerging on the social interactions between large populations of speakers. In this context, agent models provide a sound approach to investigate the complex dynamics of genetic biasing on language and speech

Abstract

Mutations of the epidermal growth factor receptor (EGFR) gene are found at a relatively high frequency in glioma, with the most common being the de2-7 EGFR (or EGFRvIII). This mutation arises from an in-frame deletion of exons 2-7, which removes 267 amino acids from the extracellular domain of the receptor. Despite being unable to bind ligand, the de2-7 EGFR is constitutively active at a low level. Transfection of human glioma cells with the de2-7 EGFR has little effect in vitro, but when grown as tumor xenografts this mutated receptor imparts a dramatic growth advantage. We mapped the phosphorylation pattern of de2-7 EGFR, both in vivo and in vitro, using a panel of antibodies specific for different phosphorylated tyrosine residues. Phosphorylation of de2-7 EGFR was detected constitutively at all tyrosine sites surveyed in vitro and in vivo, including tyrosine 845, a known target in the wild-type EGFR for src kinase. There was a substantial upregulation of phosphorylation at every yrosine residue of the de2-7 EGFR when cells were grown in vivo compared to the receptor isolated from cells cultured in vitro. Upregulation of phosphorylation at tyrosine 845 could be stimulated in vitro by the addition of specific components of the ECM via an integrindependent mechanism. These observations may partially explain why the growth enhancement mediated by de2-7 EGFR is largely restricted to the in vivo environment

Abstract

The present paper describes the development of the languagesindanger.eu interactive website as an example of including multimedia language resources to disseminate knowledge and create educational material on less-resourced languages. The website is a product of INNET (Innovative networking in infrastructure for endangered languages), European FP7 project. Its main functions can be summarized as related to the three following areas: (1) raising students' awareness of language endangerment and arouse their interest in linguistic diversity, language maintenance and language documentation; (2) informing both students and teachers about these topics and show ways how they can enlarge their knowledge further with a special emphasis on information about language archives; (3) helping teachers include these topics into their classes. The website has been localized into five language versions with the intention to be accessible to both scientific and non-scientific communities such as (primarily) secondary school teachers and students, beginning university students of linguistics, journalists, the interested public, and also members of speech communities who speak minority languages

Abstract

It has been suggested that some individuals may benefit more from social robots than do others. Using second
language (L2) as an example, the present study examined how individual differences in attitudes toward robots and personality
traits may be related to learning outcomes. Preliminary results with 24 Turkish-speaking adults suggest that negative attitudes
toward robots, more specifically thoughts and anxiety about the negative social impact that robots may have on the society,
predicted how well adults learned L2 words from a social robot. The possible implications of the findings as well as future directions are also discussed

Abstract

A wealth of studies has shown that more proficient monolingual speakers are better at predicting upcoming information during language comprehension. Similarly, prediction skills of adult second language (L2) speakers in their L2 have also been argued to be modulated by their L2 proficiency. How exactly language proficiency and prediction are linked, however, is yet to be systematically investigated. One group of language users which has the potential to provide invaluable insights into this link is bilingual children. In this paper, we compare bilingual children’s prediction skills with those of monolingual children and adult L2 speakers, and show how investigating bilingual children’s prediction skills may contribute to our understanding of how predictive processing works.

Abstract

There is a strong relation between children’s exposure to
spatial terms and their later memory accuracy. In the current
study, we tested whether the production of spatial terms by
children themselves predicts memory accuracy and whether
and how language modality of these encodings modulates
memory accuracy differently. Hearing child speakers of
Turkish and deaf child signers of Turkish Sign Language
described pictures of objects in various spatial relations to each
other and later tested for their memory accuracy of these
pictures in a surprise memory task. We found that having
described the spatial relation between the objects predicted
better memory accuracy. However, the modality of these
descriptions in sign, speech, or speech-plus-gesture did not
reveal differences in memory accuracy. We discuss the
implications of these findings for the relation between spatial
language, memory, and the modality of encoding.

Abstract

We describe a reaction time study in which listeners detected word or nonword syllable targets (e.g. zoo, trel) in sequences consisting of the target plus a consonant or syllable residue (trelsh, trelshek). The pattern of responses differed from an earlier word-spotting study with the same material, in which words were always harder to find if only a consonant residue remained. The earlier results should thus not be viewed in terms of syllabic parsing, but in terms of a universal role for syllables in speech perception; words which are accidentally present in spoken input (e.g. sell in self) can be rejected when they leave a residue of the input which could not itself be a word.