Publications

Abstract

Human actions in the social world – like greeting, requesting, complaining, accusing, asking, confirming, etc. – are recognised through the interpretation of signs. Language is where much of the action is, but gesture, facial expression and other bodily actions matter as well. The goal of this task is to establish a maximally rich description of a representative, good quality piece of conversational interaction, which will serve as a reference point for comparative exploration of the status of social actions and their formulation across language

Abstract

This paper investigates how listeners process regular pronunciation variants, resulting from simple general reduction processes. Study 1 shows that when listeners are presented with new words, they store the pronunciation variants presented to them, whether these are unreduced or reduced. Listeners thus store information on word-specific pronunciation variation. Study 2 suggests that if participants are presented with regularly reduced pronunciations, they also reconstruct and store the corresponding unreduced pronunciations. These unreduced pronunciations apparently have special status. Together the results support hybrid models of speech processing, assuming roles for both exemplars and abstract representations.

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

This chapter summarizes the extensive discussions that took place during the Forum as well as the subsequent months thereafter. It assesses current understanding of the neuronal mechanisms that underlie syntactic structure and processing.... It is posited that to understand the neurobiology of syntax, it might be worthwhile to shift the balance from comprehension to syntactic encoding in language production

Abstract

We present a neural-symbolic learning model of sentence production which displays strong semantic systematicity and recursive productivity. Using this model, we provide evidence for the data-driven learnability of complex yes/no- questions.

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

Los idiomas sudamericanas tienen una diversidad de sistemas numéricos, desde sistemas con solamente dos o tres términos en algunos idiomas amazónicos hasta sistemas con numerales extendiendo a miles. Una mirada al sistema del idioma cha’palaa de Ecuador demuestra rasgos de base-2, base-5, base-10 y base-20, ligados a diferentes etapas de cambio, desarrollo y contacto lingüístico. Conocer estas etapas nos permite proponer algunas correlaciones con lo que conocemos de la historia de contactos culturales en la región. The South American languages have diverse types of numeral systems, from systems of just two or three terms in some Amazonian languages to systems extending into the thousands. A look a the system of the Cha'palaa language of Ecuador demonstrates base-2, base-5, base-10 and base-20 features, linked to different stages of change, development and language contact. Learning about these stages permits up to propose some correlations between them and what we know about the history of cultural contact in the region.

Abstract

In a 2x2 event-related FMRI study we find support for the idea that the inferior frontal cortex, centered on Broca’s region and its homologue, is involved in constructive unification operations during the structure-building process in parsing for comprehension. Tentatively, we provide evidence for a role of the dorsolateral prefrontal cortex centered on BA 9/46 in the control component of the language system. Finally, the left temporo-parietal cortex, in the vicinity of Wernicke’s region, supports the interaction between the syntax of gender agreement and sentence-level semantics.

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

Human implicit learning can be investigated with implicit artificial grammar learning, a simple model for aspects of natural language acquisition. In this paper we investigate the remaining effect of modality transfer in syntactic classification of an acquired grammatical sequence structure after implicit grammar acquisition. Participants practiced either on acoustically presented syllable sequences or visually presented consonant letter sequences. During classification we independently manipulated the statistical frequency-based and rule-based characteristics of the classification stimuli. Participants performed reliably above chance on the within modality classification task although more so for those working on syllable sequence acquisition. These subjects were also the only group that kept a significant performance level in transfer classification. We speculate that this finding is of particular relevance in consideration of an ecological validity in the input signal in the use of artificial grammar learning and in language learning paradigms at large.

Abstract

The molecular, developmental, and evolutionary bases of human brain asymmetry are almost completely unknown. Genetic linkage and association mapping have pin-pointed a gene called LRRTM1 (leucine-rich repeat transmembrane neuronal 1) that may contribute to variability in human handedness. Here I describe how LRRTM1's involvement in handedness was discovered, and also the latest knowledge of its functions in brain development and disease. The association of LRRTM1 with handedness was derived entirely from the paternally inherited gene, and follow-up analysis of gene expression confirmed that LRRTM1 is one of a small number of genes that are imprinted in the human genome, for which the maternally inherited copy is suppressed. The same variation at LRRTM1 that was associated paternally with mixed-/left-handedness was also over-transmitted paternally to schizophrenic patients in a large family study.
LRRTM1 is expressed in specific regions of the developing and adult forebrain by post-mitotic neurons, and the protein may be involved in axonal trafficking. Thus LRRTM1 has a probable role in neurodevelopment, and its association with handedness suggests that one of its functions may be in establishing or consolidating human brain asymmetry.
LRRTM1 is the first gene for which allelic variation has been associated with human handedness. The genetic data also suggest indirectly that the epigenetic regulation of this gene may yet prove more important than DNA sequence variation for influencing brain development and disease.
Intriguingly, the parent-of-origin activity of LRRTM1 suggests that men and women have had conflicting interests in relation to the outcome of lateralized brain development in their offspring.

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

This paper presents a new architecture for optical burst switched networks where the control plane of the network functions in a cooperative manner. Each node interprets the data conveyed by the control packet and forwards it to the next nodes, making the control plane of the network distribute the relevant information to all the nodes in the network. A cooperation transmission tree is used, thus allowing all the nodes to store the information related to the traffic management in the network, and enabling better network resource planning at each node. A model of this network architecture is proposed, and its performance is evaluated.

Abstract

In this paper we introduce Functional Data Analysis (FDA) as a tool for analyzing dynamic transitions in speech signals. FDA makes it possible to perform statistical analyses of sets of mathematical functions in the same way as classical multivariate analysis treats scalar measurement data. We illustrate the use of FDA with a reduction phenomenon affecting the French word c'était /setε/ 'it was', which can be reduced to [stε] in conversational speech. FDA reveals that the dynamics of the transition from [s] to [t] in fully reduced cases may still be different from the dynamics of [s] - [t] transitions in underlying /st/ clusters such as in the word stage.

Abstract

The goal of this task is to investigate cross-cultural emotion categories in language and thought. This entry is designed to provide researchers with some guidelines to describe the emotional repertoire of a community from an emic perspective. The first objective is to offer ethnographic tools and a questionnaire in order to understand the semantics of emotional terms and the local conception of emotions. The second objective is to identify the local display rules of emotions in communicative interactions.

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

The aim of this chapter is to provide researchers with a tool kit of semi-experimental and experimental techniques for studying code-switching. It presents an overview of the current off-line and on-line research techniques, ranging from analyses of published bilingual texts of spontaneous conversations, to tightly controlled experiments. A multi-task approach used for studying code-switched sentence production in Papiamento-Dutch bilinguals is also exemplified.

Abstract

Gestures, the symbolic movements speakers perform while they speak, are systematically related to speech and language in non-trivial ways. This chapter presents an overview of what gestures can and cannot tell us about the monolingual and the bilingual mental lexicon. Gesture analysis opens for a broader view of the mental lexicon, targeting the interface between conceptual, semantic and syntactic aspects of event construal, and offers new possibilities for examining how languages co-exist and interact in bilinguals beyond the level of surface forms. The first section of this chapter gives a brief introduction to gesture studies and outlines the current views on the relationship between gesture, speech, and language. The second section targets the key questions for the study of the monolingual and bilingual lexicon, and illustrates the methods employed for addressing these questions. It further exemplifies systematic cross-linguistic patterns in gestural behaviour in monolingual and bilingual contexts. The final section discusses some implications of an expanded view of the multilingual lexicon that includes gesture, and outlines directions for future inquiry.

Abstract

This contribution focuses on the neural infrastructure for parsing and syntactic encoding. From an anatomical point of view, it is argued that Broca's area is an ill-conceived notion. Functionally, Broca's area and adjacent cortex (together Broca's complex) are relevant for language, but not exclusively for this domain of cognition. Its role can be characterized as providing the necessary infrastructure for unification (syntactic and semantic). A general proposal, but with required level of computational detail, is discussed to account for the distribution of labor between different components of the language network in the brain.Arguments are provided for the immediacy principle, which denies a privileged status for syntax in sentence processing. The temporal profile of event-related brain potential (ERP) is suggested to require predictive processing. Finally, since, next to speed, diversity is a hallmark of human languages, the language readiness of the brain might not depend on a universal, dedicated neural machinery for syntax, but rather on a shaping of the neural infrastructure of more general cognitive systems (e.g., memory, unification) in a direction that made it optimally suited for the purpose of communication through language.

Abstract

Language and communication are about the exchange of meaning. A key feature of understanding and producing language is the construction of complex meaning from more elementary semantic building blocks. The functional characteristics of this semantic unification process are revealed by studies using event related brain potentials. These studies have found that word meaning is assembled into compound meaning in not more than 500 ms. World knowledge, information about the speaker, co-occurring visual input and discourse all have an immediate impact on semantic unification, and trigger similar electrophysiological responses as sentence-internal semantic information. Neuroimaging studies show that a network of brain areas, including the left inferior frontal gyrus, the left superior/middle temporal cortex, the left inferior parietal cortex and, to a lesser extent their right hemisphere homologues are recruited to perform semantic unification.

Abstract

Two experiments were carried out to examine the syllable affiliation of intervocalic consonant clusters and their effects on speech segmentation in two different languages. In a syllable reversal task, Slovak and German speakers divided bisyllabic non-words that were presented aurally into two parts, starting with the second syllable. Following the maximal onset principle, intervocalic consonants should be maximally assigned to the onset of the following syllable in conformity with language-specific restrictions, e.g., /du.gru/, /zu.kro:/ (dot indicates a syllable boundary). According to German phonology, syllables require branching rhymes (hence, /zuk.ro:/). In Slovak, both /du.gru/ and /dug.ru/ are possible syllabifications. Experiment 1 showed that German speakers more often closed the first syllable (/zuk.ro:/), following the requirement for a branching rhyme. In Experiment 2, Slovak speakers showed no clear preference; the first syllable was either closed (/dug.ru/) or open (/du.gru/). Correlation analyses on previously conducted word-spotting studies (Hanulíková, in press, 2008) suggest that speech segmentation is unaffected by these syllabification preferences.

Abstract

Present-day sentence generators are often in-capable of producing a wide variety of well-formed elliptical versions of coordinated clauses, in particular, of combined elliptical phenomena (Gapping, Forward and Back-ward Conjunction Reduction, etc.). The ap-plicability of the various types of clausal co-ordinate ellipsis (CCE) presupposes detailed comparisons of the syntactic properties of the coordinated clauses. These nonlocal comparisons argue against approaches based on local rules that treat CCE structures as special cases of clausal coordination. We advocate an alternative approach where CCE rules take the form of postediting rules ap-plicable to nonelliptical structures. The ad-vantage is not only a higher level of modu-larity but also applicability to languages be-longing to different language families. We describe a language-neutral module (called Elleipo; implemented in JAVA) that gener-ates as output all major CCE versions of co-ordinated clauses. Elleipo takes as input linearly ordered nonelliptical coordinated clauses annotated with lexical identity and coreferentiality relationships between words and word groups in the conjuncts. We dem-onstrate the feasibility of a single set of postediting rules that attains multilingual coverage.

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

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

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 article reviews neurocognitive evidence on second language (L2) processing at speech sound, word, and sentence levels. Hemodynamic (functional magnetic resonance imaging and positron emission tomography) data suggest that L2s are implemented in the same brain structures as the native language but with quantitative differences in the strength of activation that are modulated by age of L2 acquisition and L2 proficiency. Electrophysiological data show a more complex pattern of first and L2 similarities and differences, providing some, although not conclusive, evidence for qualitative differences between L1 and L2 syntactic processing.

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

Listening to a speaker while hearing another speaker talks is a challenging task for elderly listeners. We show that elderly listeners over the age of 65 with various degrees of age-related hearing loss benefit in this situation from also seeing the speaker they intend to listen to. In a phoneme monitoring task, listeners monitored the speech of a target speaker for either the phoneme /p/ or /k/ while simultaneously hearing a competing speaker. Critically, on some trials, the target speaker was also visible. Elderly listeners benefited in their response times and accuracy levels from seeing the target speaker when monitoring for the less visible /k/, but more so when monitoring for the highly visible /p/. Visual speech therefore aids elderly listeners not only by providing segmental information about the target phoneme, but also by providing more global information that allows for better performance in this adverse listening situation.

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

Spatial terms in the world’s languages appear to reflect both universal conceptual tendencies and linguistic convention. A similarly mixed picture in the case of color naming has been accounted for in terms of near-optimal partitions of color space. Here, we demonstrate that this account generalizes to spatial terms. We show that the spatial terms of 9 diverse languages near-optimally partition a similarity space of spatial meanings, just as color terms near-optimally partition color space. This account accommodates both universal tendencies and cross-language differences in spatial category extension, and identifies general structuring principles that appear to operate across different semantic domains.

Abstract

The Max Planck Institute for Psycholinguistics (MPI) manages an archive of linguistic research data with a current size of almost 20 Terabytes. Apart from in-house researchers other projects also store their data in the archive, most notably the Documentation of Endangered Languages (DoBeS) projects. The archive is available online and can be accessed by anybody with Internet access. To be able to manage this large amount of data the MPI's technical group has developed a software suite called Language Archiving Technology (LAT) that on the one hand helps researchers and archive managers to manage the data and on the other hand helps users in enriching their primary data with additional layers. All the MPI software is Java-based and developed according to open source principles (GNU, 2007). All three major operating systems (Windows, Linux, MacOS) are supported and the software works similarly on all of them. As the archive is online, many of the tools, especially the ones for accessing the data, are browser based. Some of these browser-based tools make use of Adobe Flex to create nice-looking GUIs. The LAT suite is a complete set of management and enrichment tools, and given the interaction between the tools the result is a complete LAT software domain. Over the last 10 years, this domain has proven its functionality and use, and is being deployed to servers in other institutions. This deployment is an important step in getting the archived resources back to the members of the speech communities whose languages are documented. In the paper we give an overview of the tools of the LAT suite and we describe their functionality and role in the integrated process of archiving, management and enrichment of linguistic data.