Publications

Abstract

Reciprocity lies at the heart of social cognition, and with it so does the encoding of reciprocity in language via reciprocal constructions. Despite the prominence of strong universal claims about the semantics of reciprocal constructions, there is considerable descriptive literature on the semantics of reciprocals that seems to indicate variable coding and subtle cross-linguistic differences in meaning of reciprocals, both of which would make it impossible to formulate a single, essentialising definition of reciprocal semantics. These problems make it vital for studies in the semantic typology of reciprocals to employ methodologies that allow the relevant categories to emerge objectively from cross-linguistic comparison of standardised stimulus materials. We situate the rationale for the 20-language study that forms the basis for this book within this empirical approach to semantic typology, and summarise some of the findings.

Abstract

Reciprocals are an increasingly hot topic in linguistic research. This reflects the intersection of several factors: the semantic and syntactic complexity of reciprocal constructions, their centrality to some key points of linguistic theorizing (such as Binding Conditions on anaphors within Government and Binding Theory), and the centrality of reciprocity to theories of social structure, human evolution and social cognition. No existing work, however, tackles the question of exactly what reciprocal constructions mean cross-linguistically. Is there a single, Platonic ‘reciprocal’ meaning found in all languages, or is there a cluster of related concepts which are nonetheless impossible to characterize in any single way? That is the central goal of this volume, and it develops and explains new techniques for tackling this question. At the same time, it confronts a more general problem facing semantic typology: how to investigate a category cross-linguistically without pre-loading the definition of the phenomenon on the basis of what is found in more familiar languages.

Abstract

Relative clause processing depends on the grammatical role of the head noun in the subordinate clause. This has traditionally been explained in terms of cognitive limitations. We suggest that structure-related processing differences arise from differences in experience with these structures. We present a connectionist model which learns to produce utterances with relative clauses from exposure to message-sentence pairs. The model shows how various factors such as frequent subsequences, structural variations, and meaning conspire to create differences in the processing of these structures. The predictions of this learning-based account have been confirmed in behavioral studies with adults. This work shows that structural regularities that govern relative clause processing can be explained within a usage-based approach to recursion.

Abstract

Language acquisition involves learning nonadjacent dependencies that can obtain between words in a sentence. Several artificial grammar learning studies have shown that the ability of adults and children to detect dependencies between A and B in frames AXB is influenced by the amount of variation in the X element. This paper presents a model of statistical learning which displays similar behavior on this task and generalizes in a human-like way. The model was also used to predict human behavior for increased distance and more variation in dependencies. We compare our model-based approach with the standard invariance account of the variability effect.

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

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

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

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

Using a poorly mastered second language (L2) in interaction with a native speaker is a challenging task. This paper explores how L2 speakers and their native interlocutors together deploy gestures and speech to sustain problematic interaction. Drawing on native and non-native interactions in Swedish, French, and Dutch, I examine lexical, grammatical and interaction-related problems in turn. The analyses reveal that (a) different problems yield behaviours with different formal and interactive properties that are common across the language pairs and the participant roles; (b) native and non-native behaviour differs in degree, not in kind; and (c) that individual communicative style determines behaviour more than the gravity of the linguistic problem. I discuss the implications for theories opposing 'efficient' L2 communication to learning. Also, contra the traditional view of compensatory gestures, I will argue for a multi-functional 'hydraulic' view grounded in gesture theory where speech and gesture are equal partners, but where the weight carried by the modalities shifts depending on expressive pressures.

Abstract

This study focuses on the effect of the semantics of placement verbs on placement event representations. Specifically, it explores to what extent the semantic properties of habitually used verbs guide attention to certain types of spatial information. French, which typically uses a general placement verb (mettre, 'put'), is contrasted with Dutch, which uses a set of fine-grained (semi-)obligatory posture verbs (zetten, leggen, 'set/stand', 'lay'). Analysis of the concomitant gesture production in the two languages reveals a patterning toward two distinct, language-specific event representations. The object being placed is an essential part of the Dutch representation, while French speakers instead focus only on the (path of the) placement movement. These perspectives permeate the entire placement domain regardless of the actual verb used.

Abstract

A key problem in studies of bilingual linguistic cognition is how to probe the details of underlying representations in order to gauge whether bilinguals' conceptualizations differ from those of monolinguals, and if so how. This chapter provides an overview of a line of studies that rely on speech-associated gestures to explore these issues. The gestures of adult monolingual native speakers differ systematically across languages, reflecting consistent differences in what information is selected for expression and how it is mapped onto morphosyntactic devices. Given such differences, gestures can provide more detailed information on how multilingual speakers conceptualize events treated differently in their respective languages, and therefore, ultimately, on the nature of their representations. This chapter reviews a series of studies in the domain of (voluntary and caused) motion event construal. I first discuss speech and gesture evidence for different construals in monolingual native speakers, then review studies on second language speakers showing gestural evidence of persistent L1 construals, shifts to L2 construals, and of bidirectional influences. I consider the implications for theories of ultimate attainment in SLA, transfer and convergence. I will also discuss the methodological implications, namely what gesture data do and do not reveal about linguistic conceptualisation and linguistic relativity proper.

Abstract

The present paper considers the problem of annotating bibliographical references with labels/classes, given training data of references already annotated with labels. The problem is an instance of document categorization where the documents are short and written in a wide variety of languages. The skewed distributions of title words and labels calls for special carefulness when choosing a Machine Learning approach. The present paper describes how to induce Disjunctive Normal Form formulae (DNFs), which have several advantages over Decision Trees. The approach is evaluated on a large real-world collection of bibliographical references.

Abstract

This corpus study demonstrates that the realization of wordfinal /t/ in Dutch past-participles in various speech styles is affected by a word’s predictability and paradigmatic relative frequency. In particular, /t/s are shorter and more often absent if the two preceding words are more predictable. In addition, /t/s, especially in irregular verbs, are more reduced, the lower the verb’s lemma frequency relative to the past-participle’s frequency. Both effects are more pronounced in more spontaneous speech. These findings are expected if speech planning plays an important role in speech reduction. Index Terms: pronunciation variation, acoustic reduction, corpus research, word predictability, morphological decomposability

Abstract

Students who are learning to write in a foreign language, often want feedback on the grammatical quality of the sentences they produce. The usual NLP approach to this problem is based on parsing student-generated text. Here, we propose a generation-based ap- proach aiming at preventing errors ("scaffolding"). In our ICALL system, the student constructs sentences by composing syntactic trees out of lexically anchored "treelets" via a graphical drag & drop user interface. A natural-language generator computes all possible grammatically well-formed sentences entailed by the student-composed tree. It provides positive feedback if the student-composed tree belongs to the well-formed set, and negative feedback otherwise. If so requested by the student, it can substantiate the positive or negative feedback based on a comparison between the student-composed tree and its own trees (informative feedback on demand). In case of negative feedback, the system refuses to build the structure attempted by the student. Frequently occurring errors are handled in terms of "malrules." The system we describe is a prototype (implemented in JAVA and C++) which can be parameterized with respect to L1 and L2, the size of the lexicon, and the level of detail of the visually presented grammatical structures.

Abstract

Cross-culturally, the human mind varies more than we generally assume

Abstract

Contemporary comparative cognition has a large repertoire of animal models and methods, with concurrent theoretical advances that are providing initial answers to crucial questions about human cognition. What cognitive traits are uniquely human? What are the species-typical inherited predispositions of the human mind? What is the human mind capable of without certain types of specific experiences with the surrounding environment? Here, we review recent findings from the domains of space, time and number cognition. These findings are produced using different comparative methodologies relying on different animal species, namely birds and non-human great apes. The study of these species not only reveals the range of cognitive abilities across vertebrates, but also increases our understanding of human cognition in crucial ways.

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

This study uses a classical referential communication task to
investigate the role of co-speech gestures in the process of
coordination. The study manipulates both the common ground between the interlocutors, as well as the visibility of the gestures they use. The findings show that co-speech gestures are an integral part of the referential utterances speakers
produced with regard to both initial references as well as repeated references, and that the availability of gestures appears to impact on interlocutors’ referential oordination. The results are discussed with regard to past research on
common ground as well as theories of gesture production.

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

The current chapter discusses a structural priming experiment that investigated the on-line processing of English subject- and object- relative clauses. Sixty-one monolingual English-speaking adults participated in a self-paced reading experiment where they read prime-target pairs that fully crossed the relativised element within the relative clause (subject- versus object) across prime and target sentences. Following probabilistic theories of sentence processing, which predict that low frequency structures like object relatives are subject to greater priming effects due to their marked status, it was hypothesised that the normally-observed subject RC processing advantage would be eliminated following priming. The hypothesis was supported, identifying an important role for structural frequency in the processing of relative clause structures.

Abstract

The aim of this paper is to discuss an inherent difficulty of PET (and fMRI) research in language production. On the one hand, language production presupposes some degree of freedom for the subject, on the other hand, interpretability of results presupposes restrictions of this freedom. This difficulty is reflected in the existing PET literature in some neglect of the general principle to design experiments in such a way that the results do not allow for alternative interpretations. It is argued that by narrowing down the scope of experiments a gain in interpretability can be achieved.

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

We investigated whether seeing a pointing gesture influences the perceived lexical stress. A pitch contour continuum between the Dutch words “CAnon” (‘canon’) and “kaNON” (‘cannon’) was presented along with a pointing gesture during the first or the second syllable. Pointing gestures following natural recordings but not Gaussian functions influenced stress perception (Experiment 1 and 2), especially when auditory context preceded (Experiment 2). This was not replicated in Experiment 3. Natural pointing gestures failed to affect the categorization of a pitch peak timing continuum (Experiment 4). There is thus no convincing evidence that seeing a pointing gesture influences lexical stress perception.

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

The psychological process of translating semantic into syntactic structures has dynamic properties such as the following. (1) The speaker is able to start pronouncing an utterance before having worked out the semantic content he wishes to express. Selection of semantic content and construction of syntactic form proceed partially in parallel. (2) The human sentence generator takes as input not only a specification of semantic content but also some indication of desired syntactic shape. Such indications, if present, do not complicate the generation process but make it easier. (3) Certain regularities of speech errors suggest a two-stage generation process. Stage I constructs the “syntactic skeleton” of an utterance; stage II provides the skeleton with morpho- honological information. An outline is given of the type of grammar which is used by a sentence generation system embodying these characteristics. The system is being implemented on a computer.

Abstract

Rede, uitgesproken bij de aanvaarding van het ambt van lector in de taalpsychologie aan de Katholieke Universiteit te Nijmegen op Vrijdag 10 juni 1977

Abstract

[Seven one-page psycholinguistic sketches]

Abstract

The psychological process of producing sentences includes conceptualization (selecting to-beexpressed conceptual content) and formulation (translating conceptual content into syntactic structures of a language). There is ample evidence, both intuitive and experimental, that the conceptualizing and formulating processes often proceed concurrently, not strictly serially. James Lindsley (Cognitive Psych.,1975, 7, 1-19; J.Psycholinguistic Res., 1976, 5, 331-354) has developed a concurrent model which proved succesful in an experimental situation where simple English Subject-Verb (SV) sentences such as “The boy is greeting”,”The girl is kicking” were produced as descriptions of pictures which showed actor and action. The measurements were reaction times defined as the interval between the moment a picture appeared on a screen and the onset of the vocal utterance by the speaker. Lindsley could show, among other things, that the formulation process for an SV sentence doesn’t start immediately after the actor of a picture (that is, the conceptual content underlying the surface Subject phrase) has been identified, but is somewhat delayed. The delay was needed, according to Lindsley, in order to prevent dysfluencies (hesitations) between surface Subject and verb. We replicated Lindsley’s data for Dutch. However, his model proved inadequate when we added Dutch Verb-Subject (VS) constructions which are obligatory in certain syntactic contexts but synonymous with their SV counterparts. A sentence production theory which is being developed by the first author is able to provide an accurate account of the data. The abovementioned delay is attributed to certain precautions the sentence generator has to take in case of SV but not of VS sentences. These precautions are related to the goal of attaining syntactic coherence of the utterance as a whole, not to the prevention of dysfluencies.

Abstract

The volume presents an essential selection collected from the essays of Wolfgang Klein. In addition to journal and book articles, many of them published by Mouton, this book features new and unpublished texts by the author. It focuses, among other topics, on information structure, the expression of grammatical categories and the structure of learner varieties.

Abstract

Words can be distinguished by segmental differences or by suprasegmental differences or both. Studies from English suggest that suprasegmentals play little role in human spoken-word recognition; English stress, however, is nearly always unambiguously coded in segmental structure (vowel quality); this relationship is less close in Dutch. The present study directly compared the effects of segmental and suprasegmental mispronunciation on word recognition in Dutch. There was a strong effect of suprasegmental mispronunciation, suggesting that Dutch listeners do exploit suprasegmental information in word recognition. Previous findings indicating the effects of mis-stressing for Dutch differ with stress position were replicated only when segmental change was involved, suggesting that this is an effect of segmental rather than suprasegmental processing.

Abstract

Citations play a crucial role in the scientific discourse, in information retrieval, and in bibliometrics. Many initiatives are currently promoting the idea of having free and open citation data. Creation of citation data, however, is not part of the cataloging workflow in libraries nowadays.
In this paper, we present our project Linked Open Citation Database, in which we design distributed processes and a system infrastructure based on linked data technology. The goal is to show that efficiently cataloging citations in libraries using a semi-automatic approach is possible. We specifically describe the current state of the workflow and its implementation. We show that we could significantly improve the automatic reference extraction that is crucial for the subsequent data curation. We further give insights on the curation and linking process and provide evaluation results that not only direct the further development of the project, but also allow us to discuss its overall feasibility.

Abstract

It is widely held that smells and flavors are impossible to put into words. In this paper we test this claim by seeking predictive patterns in wine reviews, which ostensibly aim to provide guides to perceptual content. Wine reviews have previously been critiqued as random and meaningless. We collected an English corpus of wine reviews with their structured metadata, and applied machine learning techniques to automatically predict the wine's color, grape variety, and country of origin. To train the three supervised classifiers, three different information sources were incorporated: lexical bag-of-words features, domain-specific terminology features, and semantic word embedding features. In addition, using regression analysis we investigated basic review properties, i.e., review length, average word length, and their relationship to the scalar values of price and review score. Our results show that wine experts do share a common vocabulary to describe wines and they use this in a consistent way, which makes it possible to automatically predict wine characteristics based on the review text alone. This means that odors and flavors may be more expressible in language than typically acknowledged.

Abstract

Annotations of media recordings are the grounds for linguistic research. Since creating those annotations is a very laborious task, reaching 100 times longer than the length of the annotated media, innovative audio and video processing algorithms are needed, in order to improve the efficiency and quality of annotation process. The AVATecH project, started by the Max-Planck Institute for Psycholinguistics (MPI) and the Fraunhofer institutes HHI and IAIS, aims at significantly speeding up the process of creating annotations of audio-visual data for humanities research. In order for this to be achieved a range of state-of-the-art audio and video pattern recognition algorithms have been developed and integrated into widely used ELAN annotation tool. To address the problem of heterogeneous annotation tasks and recordings we provide modular components extended by adaptation and feedback mechanisms to achieve competitive annotation quality within significantly less annotation time.

Abstract

Evolution and changes of all modern languages is a well-known fact. However, recently it is reaching dynamics never seen before, which results in loss of the vast amount of information encoded in every language. In order to preserve such heritage, properly annotated recordings of world languages are necessary. Since creating those annotations is a very laborious task, reaching times 100 longer than the length of the annotated media, innovative video processing algorithms are needed, in order to improve the efficiency and quality of annotation process.

Abstract

Processing medical data has always been an interesting field that has shown the need for effective image segmentation methods. Modern medical image segmentation solutions are focused on 3D image volumes, which originate at advanced acquisition devices. Operating on such data in a 3D envi- ronment is essential in order to take the full advantage of the available information. In this paper we present an extended version of our 3D image segmentation and reconstruction model that belongs to the family of Deformable Models and is capable of processing large image volumes in competitive times and in fully 3D environment, offering a big level of automation of the process and a high precision of results. It is also capable of handling topology changes and offers a very good scalability on multi-processing unit architectures. We present a description of the model and show its capabilities in the field of medical image processing.

Abstract

Reproduced with permission of Blackwell Publishing from: Levinson, S. C. (2004) 'Deixis'. In: Horn, L.R. and Ward, G. (Eds.) The Handbook of Pragmatics. Oxford: Blackwell Publishing, pp. 100-121