Publications

Abstract

In conversation, people regularly deal with problems of speaking, hearing, and understanding. We report on a cross-linguistic investigation of the conversational structure of other-initiated repair (also known as collaborative repair, feedback, requests for clarification, or grounding sequences). We take stock of formats for initiating repair across languages (comparable to English huh?, who?, y’mean X?, etc.) and find that different languages make available a wide but remarkably similar range of linguistic resources for this function. We exploit the patterned variation as evidence for several underlying concerns addressed by repair initiation: characterising trouble, managing responsibility, and handling knowledge. The concerns do not always point in the same direction and thus provide participants in interaction with alternative principles for selecting one format over possible others. By comparing conversational structures across languages, this paper contributes to pragmatic typology: the typology of systems of language use and the principles that shape them.

Abstract

Linguistic discovery is viewpoint-dependent, just like our ideas about what is marginal and what is central in language. In this essay I consider two supposed marginalia —ideophones and interjections— which provide some useful pointers for widening our field of view. Ideophones challenge us to take a fresh look at language and consider how it is that our communication system combines multiple modes of representation. Interjections challenge us to extend linguistic inquiry beyond sentence level, and remind us that language is social-interactive at core. Marginalia, then, are not the obscure, exotic phenomena that can be safely ignored: they represent opportunities for innovation and invite us to keep pushing the edges of linguistic inquiry.

Abstract

Numerous experiments show that space and musical pitch are
closely linked in people's minds. However, the exact nature of
space-pitch associations and their neuronal underpinnings are
not well understood. In an fMRI experiment we investigated
different types of spatial representations that may underlie
musical pitch. Participants judged stimuli that varied in
spatial height in both the visual and tactile modalities, as well
as auditory stimuli that varied in pitch height. In order to
distinguish between unimodal and multimodal spatial bases of
musical pitch, we examined whether pitch activations were
present in modality-specific (visual or tactile) versus
multimodal (visual and tactile) regions active during spatial
height processing. Judgments of musical pitch were found to
activate unimodal visual areas, suggesting that space-pitch
associations may involve modality-specific spatial
representations, supporting a key assumption of embodied
theories of metaphorical mental representation.

Abstract

Responding to similarity, difference, and relative magnitude (SDM) is ubiquitous in the animal kingdom. However, humans seem unique in the ability to represent relative magnitude (‘more’/‘less’) and similarity (‘same’/‘different’) as abstract relations that take arguments (e.g., greater-than (x,y)). While many models use structured relational representations of magnitude and similarity, little progress has been made on how these representations arise. Models that developuse these representations assume access to computations of similarity and magnitude a priori, either encoded as features or as output of evaluation operators. We detail a mechanism for producing invariant responses to “same”, “different”, “more”, and “less” which can be exploited to compute similarity and magnitude as an evaluation operator. Using DORA (Doumas, Hummel, & Sandhofer, 2008), these invariant responses can serve be used to learn structured relational representations of relative magnitude and similarity from pixel images of simple shapes

Abstract

This paper summarizes the results of a descriptive syntactic category analysis of child English no which reveals that young children use and represent no as a determiner and negatives like no pen as NPs, contra standard analyses.

Abstract

Previous studies have demonstrated that native listeners
modify their interpretation of a speech sound when a talker
produces an ambiguous sound in order to quickly tune into a
speaker, but there is hardly any evidence that non-native
listeners employ a similar mechanism when encountering
ambiguous pronunciations. So far, one study demonstrated
this lexically-guided perceptual learning effect for nonnatives,
using phoneme categories similar in the native
language of the listeners and the non-native language of the
stimulus materials. The present study investigates the question
whether phoneme category retuning is possible in a nonnative
language for a contrast, /l/-/r/, which is phonetically
differently embedded in the native (Dutch) and nonnative
(English) languages involved. Listening experiments indeed
showed a lexically-guided perceptual learning effect.
Assuming that Dutch listeners have different phoneme
categories for the native Dutch and non-native English /r/, as
marked differences between the languages exist for /r/, these
results, for the first time, seem to suggest that listeners are not
only able to retune their native phoneme categories but also
their non-native phoneme categories to include ambiguous
pronunciations.

Abstract

Biologically inspired spiking networks are an important tool to study the nature of computation and cognition in neural systems. In this work, we investigate the representational capacity of spiking networks engaged in an identity mapping task. We compare two schemes for encoding symbolic input, one in which input is injected as a direct current and one where input is delivered as a spatio-temporal spike pattern. We test the ability of networks to discriminate their input as a function of the number of distinct input symbols. We also compare performance using either membrane potentials or filtered spike trains as state variable. Furthermore, we investigate how the circuit behavior depends on the balance between excitation and inhibition, and the degree of synchrony and regularity in its internal dynamics. Finally, we compare different linear methods of decoding population activity onto desired target labels. Overall, our results suggest that even this simple mapping task is strongly influenced by design choices on input encoding, state-variables, circuit characteristics and decoding methods, and these factors can interact in complex ways. This work highlights the importance of constraining computational network models of behavior by available neurobiological evidence.

Abstract

We report the results of a large-scale (N=1571) experiment to investigate whether spoken words can emerge from the process of repeated imitation. Participants played a version of the children’s game “Telephone”. The first generation was asked to imitate recognizable environmental sounds (e.g., glass breaking, water splashing); subsequent generations imitated the imitators for a total of 8 generations. We then examined whether the vocal imitations became more stable and word-like, retained a resemblance to the original sound, and became more suitable as learned category labels. The results showed (1) the imitations became progressively more word-like, (2) even after 8 generations, they could be matched above chance to the environmental sound that motivated them, and (3) imitations from later generations were more effective as learned category labels. These results show how repeated imitation can create progressively more word-like forms while retaining a semblance of iconicity.

Abstract

Previous studies have shown that speakers align their speech to each other at multiple linguistic levels. This study investigates whether alignment is mostly the result of priming from the immediately preceding
speech materials, focussing on pitch and articulation rate (AR). Native Dutch speakers completed sentences, first by themselves (pre-test), then in alternation with Confederate 1 (Round 1), with Confederate 2 (Round 2), with Confederate 1 again
(Round 3), and lastly by themselves again (post-test). Results indicate that participants aligned to the confederates and that this alignment lasted during the post-test. The confederates’ directly preceding sentences were not good predictors for the participants’ pitch and AR. Overall, the results indicate that alignment is more of a global effect than a local priming effect.

Abstract

This chapter reviews the computational processes that are responsible for recognizing word forms in the speech stream. We outline the different stages in a processing hierarchy from the extraction of general acoustic features, through speech‐specific prelexical processes, to the retrieval and selection of lexical representations. We argue that two recurring properties of the system as a whole are abstraction and adaptability. We also present evidence for parallel processing of information on different timescales, more specifically that segmental material in the speech stream (its consonants and vowels) is processed in parallel with suprasegmental material (the prosodic structures of spoken words). We consider evidence from both psycholinguistics and neurobiology wherever possible, and discuss how the two fields are beginning to address common computational problems. The challenge for future research in speech perception will be to build an account that links these computational problems, through functional mechanisms that address them, to neurobiological implementation.

Abstract

This chapter discusses some of the elements of human sociality that serve as the social and cognitive infrastructure or preconditions for the use of requests and other kinds of recruitments in interaction. The notion of an agent with goals is a canonical starting point, though importantly agency tends not to be wholly located in individuals, but rather is socially distributed. This is well illustrated in the case of requests, in which the person or group that has a certain goal is not necessarily the one who carries out the behavior towards that goal. The chapter focuses on the role of semiotic (mostly linguistic) resources in negotiating the distribution of agency with request-like actions, with examples from video-recorded interaction in Lao, a language spoken in Laos and nearby countries. The examples illustrate five hallmarks of requesting in human interaction, which show some ways in which our ‘manipulation’ of other people is quite unlike our manipulation of tools: (1) that even though B is being manipulated, B wants to help, (2) that while A is manipulating B now, A may be manipulated in return later; (3) that the goal of the behavior may be shared between A and B, (4) that B may not comply, or may comply differently than requested, due to actual or potential contingencies, and (5) that A and B are accountable to one another; reasons may be asked for, and/or given, for the request. These hallmarks of requesting are grounded in a prosocial framework of human agency.

Abstract

Over the decades, high-intensity language learners scattered over the globe referred to as “hyperpolyglots” have undertaken a natural experiment into the limits of learning and acquiring proficiencies in multiple languages. This chapter details several ways in which hyperpolyglots are relevant to research on aptitude. First, historical hyperpolyglots Cardinal Giuseppe Mezzofanti, Emil Krebs, Elihu Burritt, and Lomb Kató are described in terms of how they viewed their own exceptional outcomes. Next, I draw on results from an online survey with 390 individuals to explore how contemporary hyperpolyglots consider the explanatory value of aptitude. Third, the challenges involved in studying the genetic basis of hyperpolyglottism (and by extension of language aptitude) are discussed. This mosaic of data is meant to inform the direction of future aptitude research that takes hyperpolyglots, one type of exceptional language learner and user, into account.

Abstract

This article introduces a new speech corpus, the Nijmegen Corpus of Casual Czech (NCCCz), which contains more than 30 hours of high-quality recordings of casual conversations in Common Czech, among ten groups of three male and ten groups of three female friends. All speakers were native speakers of Czech, raised in Prague or in the region of Central Bohemia, and were between 19 and 26 years old. Every group of speakers consisted of one confederate, who was instructed to keep the conversations lively, and two speakers naive to the purposes of the recordings. The naive speakers were engaged in conversations for approximately 90 minutes, while the confederate joined them for approximately the last 72 minutes. The corpus was orthographically annotated by experienced transcribers and this orthographic transcription was aligned with the speech signal. In addition, the conversations were videotaped. This corpus can form the basis for all types of research on casual conversations in Czech, including phonetic research and research on how to improve automatic speech recognition. The corpus will be freely available

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 paper shows that the dictation task, a well-
known testing instrument in language education, has
untapped potential as a research tool for studying
speech perception. We describe how transcriptions
can be scored on measures of lexical, orthographic,
phonological, and semantic similarity to target
phrases to provide comprehensive information about
accuracy at different processing levels. The former
three measures are automatically extractable,
increasing objectivity, and the middle two are
gradient, providing finer-grained information than
traditionally used. We evaluate the measures in an
English dictation task featuring phonetically reduced
continuous speech. Whereas the lexical and
orthographic measures emphasize listeners’ word
identification difficulties, the phonological measure
demonstrates that listeners can often still recover
phonological features, and the semantic measure
captures their ability to get the gist of the utterances.
Correlational analyses and a discussion of practical
and theoretical considerations show that combining
multiple measures improves the dictation task’s
utility as a research tool.

Abstract

Lexically guided perceptual learning has traditionally been studied with ambiguous consonant sounds to which native listeners are exposed in a purely receptive listening context. To extend previous research, we investigate whether lexically guided learning applies to a vowel shift encountered by non-native listeners in an interactive dialogue. Dutch participants played a two-player game in English in either a control condition, which contained no evidence for a vowel shift, or a lexically constraining condition, in which onscreen lexical information required them to re-interpret their interlocutor’s /ɪ/ pronunciations as representing /ε/. A phonetic categorization pre-test and post-test were used to assess whether the game shifted listeners’ phonemic boundaries such that more of the /ε/-/ɪ/ continuum came to be perceived as /ε/. Both listener groups showed an overall post-test shift toward /ɪ/, suggesting that vowel perception may be sensitive to directional biases related to properties of the speaker’s vowel space. Importantly, listeners in the lexically constraining condition made relatively more post-test /ε/ responses than the control group, thereby exhibiting an effect of lexically guided adaptation. The results thus demonstrate that non-native listeners can adjust their phonemic boundaries on the basis of lexical information to accommodate a vowel shift learned in interactive conversation.

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

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

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

One of the most daunting tasks of a listener is to map a
continuous auditory stream onto known speech sound
categories and lexical items. A major issue with this mapping
problem is the variability in the acoustic realizations of sound
categories, both within and across speakers. Past research has
suggested listeners may use visual information (e.g., lipreading)
to calibrate these speech categories to the current
speaker. Previous studies have focused on audiovisual
recalibration of consonant categories. The present study
explores whether vowel categorization, which is known to show
less sharply defined category boundaries, also benefit from
visual cues.
Participants were exposed to videos of a speaker
pronouncing one out of two vowels, paired with audio that was
ambiguous between the two vowels. After exposure, it was
found that participants had recalibrated their vowel categories.
In addition, individual variability in audiovisual recalibration is
discussed. It is suggested that listeners’ category sharpness may
be related to the weight they assign to visual information in
audiovisual speech perception. Specifically, listeners with less
sharp categories assign more weight to visual information
during audiovisual speech recognition.

Abstract

Achieving linguistic proficiency requires identifying words from speech, and discovering the constraints that govern the way those words are used. In a recent study of non-adjacent dependency learning, Frost and Monaghan (2016) demonstrated that learners may perform these tasks together, using similar statistical processes - contrary to prior suggestions. However, in their study, non-adjacent dependencies were marked by phonological cues (plosive-continuant-plosive structure), which may have influenced learning. Here, we test the necessity of these cues by comparing learning across three conditions; fixed phonology, which contains these cues, varied phonology, which omits them, and shapes, which uses visual shape sequences to assess the generality of statistical processing for these tasks. Participants segmented the sequences and generalized the structure in both auditory conditions, but learning was best when phonological cues were present. Learning was around chance on both tasks for the visual shapes group, indicating statistical processing may critically differ across domains.

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

A crucial aspect of everyday conversational interactions is our ability to establish and maintain common ground. Understanding the relevant mechanisms involved in such social coordination remains an important challenge for cognitive science. While common ground is often discussed in very general terms, different contexts of interaction are likely to afford different coordination mechanisms. In this paper, we investigate the presence and relation of three mechanisms of social coordination – backchannels, interactive alignment and conversational repair – across free and task-oriented conversations. We find significant differences: task-oriented conversations involve higher presence of repair – restricted offers in particular – and backchannel, as well as a reduced level of lexical and syntactic alignment. We find that restricted repair is associated with lexical alignment and open repair with backchannels. Our findings highlight the need to explicitly assess several mechanisms at once and to investigate diverse activities to understand their role and relations.

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

Large-scale graph data in real-world applications is often not static but dynamic,
i. e., new nodes and edges appear over time. Current graph convolution approaches
are promising, especially, when all the graph’s nodes and edges are available dur-
ing training. When unseen nodes and edges are inserted after training, it is not
yet evaluated whether up-training or re-training from scratch is preferable. We
construct an experimental setup, in which we insert previously unseen nodes and
edges after training and conduct a limited amount of inference epochs. In this
setup, we compare adapting pretrained graph neural networks against retraining
from scratch. Our results show that pretrained models yield high accuracy scores
on the unseen nodes and that pretraining is preferable over retraining from scratch.
Our experiments represent a first step to evaluate and develop truly online variants
of graph neural networks.

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

We conduct the first systematic comparison of automated semantic
annotation based on either the full-text or only on the title metadata
of documents. Apart from the prominent text classification baselines
kNN and SVM, we also compare recent techniques of Learning
to Rank and neural networks and revisit the traditional methods
logistic regression, Rocchio, and Naive Bayes. Across three of our
four datasets, the performance of the classifications using only titles
reaches over 90% of the quality compared to the performance when
using the full-text.

Abstract

We assess the suitability of word embeddings for practical information retrieval scenarios. Thus, we assume that users issue ad-hoc short queries where we return the first twenty retrieved documents after applying a boolean matching operation between the query and the documents. We compare the performance of several techniques that leverage word embeddings in the retrieval models to compute the similarity between the query and the documents, namely word centroid similarity, paragraph vectors, Word Mover’s distance, as well as our novel inverse document frequency (IDF) re-weighted word centroid similarity. We evaluate the performance using the ranking metrics mean average precision, mean reciprocal rank, and normalized discounted cumulative gain. Additionally, we inspect the retrieval models’ sensitivity to document length by using either only the title or the full-text of the documents for the retrieval task. We conclude that word centroid similarity is the best competitor to state-of-the-art retrieval models. It can be further improved by re-weighting the word frequencies with IDF before aggregating the respective word vectors of the embedding. The proposed cosine similarity of IDF re-weighted word vectors is competitive to the TF-IDF baseline and even outperforms it in case of the news domain with a relative percentage of 15%.

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

Reading is a cultural invention that needs to recruit cortical infrastructure that was not designed for it (cultural recycling of cortical maps). In the case of reading both visual cortex and networks for speech processing are recruited. Here I discuss current views on the neurobiological underpinnings of spoken language that deviate in a number of ways from the classical Wernicke-Lichtheim-Geschwind model. More areas than Broca’s and Wernicke’s region are involved in language. Moreover, a division along the axis of language production and language comprehension does not seem to be warranted. Instead, for central aspects of language processing neural infrastructure is shared between production and comprehension. Arguments are presented in favor of a dynamic network view, in which the functionality of a region is co-determined by the network of regions in which it is embedded at particular moments in time. Finally, core regions of language processing need to interact with other networks (e.g. the attentional networks and the ToM network) to establish full functionality of language and communication. The consequences of this architecture for reading are discussed.

Abstract

Child songs are a great source for linguistic learning. Here we explore whether children can acquire novel words in a second language by playing a game featuring child songs in a playhouse. We present data from three studies that serve as scientific proof for the functionality of one game of the playhouse: the Energy Center. For this game, three hand-bikes were mounted on a panel. When children start moving the hand-bikes, child songs start playing simultaneously. Once the children produce enough energy with the hand-bikes, the songs are additionally accompanied with the sounds of musical instruments. In our studies, children executed a picture-selection task to evaluate whether they acquired new vocabulary from the songs presented during the game. Two of our studies were run in the field, one at a Dutch and one at an Indian pre-school. The third study features data from a more controlled laboratory setting. Our results partly confirm that the Energy Center is a successful means to support vocabulary acquisition in a second language. More research with larger sample sizes and longer access to the Energy Center is needed to evaluate the overall functionality of the game. Based on informal observations at our test sites, however, we are certain that children do pick up linguistic content from the songs during play, as many of the children repeat words and phrases from songs they heard. We will pick up upon these promising observations during future studies

Abstract

This chapter aims to provide an updated list of all Bantu languages known at present and to provide individual pointers to further information on the inventory. The area division has some correlation with what are perceived genealogical relations between Bantu languages, but they are not defined as such and do not change whenever there is an update in our understanding of genealogical relations. Given the popularity of Guthrie codes in Bantu linguistics, our listing also features a complete mapping to Guthrie codes. The language inventory listed excludes sign languages used in the Bantu area, speech registers, pidgins, drummed/whistled languages and urban youth languages. Pointers to such languages in the Bantu area are included in the continent-wide overview in Hammarstrom. The most important alternative names, subvarieties and spelling variants are given for each language, though such lists are necessarily incomplete and reflect some degree of arbitrary selection.

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

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

Prediction in language has traditionally been studied using
simple designs in which neural responses to expected
and unexpected words are compared in a categorical
fashion. However, these designs have been contested
as being ‘prediction encouraging’, potentially exaggerating
the importance of prediction in language understanding.
A few recent studies have begun to address
these worries by using model-based approaches to probe
the effects of linguistic predictability in naturalistic stimuli
(e.g. continuous narrative). However, these studies
so far only looked at very local forms of prediction, using
models that take no more than the prior two words into
account when computing a word’s predictability. Here,
we extend this approach using a state-of-the-art neural
language model that can take roughly 500 times longer
linguistic contexts into account. Predictability estimates
fromthe neural network offer amuch better fit to EEG data
from subjects listening to naturalistic narrative than simpler
models, and reveal strong surprise responses akin to
the P200 and N400. These results show that predictability
effects in language are not a side-effect of simple designs,
and demonstrate the practical use of recent advances
in AI for the cognitive neuroscience of language.

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

Until recently, the literature on common ground depicted its influence as a purely verbal phenomenon. We review current research on how common ground influences gesture. With informative exceptions, most experiments found that speakers used fewer gestures as well as fewer words in common ground contexts; i.e., the gesture/word ratio did not change. Common ground often led to more poorly articulated gestures, which parallels its effect on words. These findings support the principle of recipient design as well as more specific social functions such as grounding, the given-new contract, and Grice’s maxims. However, conceptual pacts or linking old with new information may maintain the original form. All together, these findings implicate gesture-speech ensembles rather than isolated effects on gestures alone.