Publications

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

The ethnographic literature has sometimes described parts of the northwest Amazon as areas of shared culture across linguistic groups. This paper illustrates how a principle of semantic transparency across languages is a key means of establishing elements of a common regional culture through practices like the calquing of ethnonyms and toponyms so that they are semantically, but not phonologically, equivalent across languages. It places the upper Rio Negro area of the northwest Amazon in a general discussion of cross-linguistic naming practices in South America and considers the extent to which a preference for semantic transparency can be linked to cases of widespread cultural ‘calquing’, in which culturally-important meanings are kept similar across different linguistic systems. It also addresses the principle of semantic transparency beyond specific referential phrases and into larger discourse structures. It concludes that an attention to semiotic practices in multilingual settings can provide new and more complex ways of thinking about the idea of shared culture.

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

This study aims to test a prediction of recent
theoretical frameworks in speech motor control: if speech production targets are specified in auditory
terms, people with better auditory acuity should have more precise speech targets.
To investigate this, we had participants perform speech perception and production tasks in a counterbalanced order. To assess speech perception acuity, we used an adaptive speech discrimination
task. To assess variability in speech production, participants performed a pseudo-word reading task; formant values were measured for each recording.
We predicted that speech production variability to correlate inversely with discrimination performance.
The results suggest that people do vary in their production and perceptual abilities, and that better discriminators have more distinctive vowel production targets, confirming our prediction. This
study highlights the importance of individual
differences in the study of speech motor control, and sheds light on speech production-perception interaction.

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

We propose a Random-Forest based sign language identification system. The system uses low-level visual features and is based on the hypothesis that sign languages have varying distributions of phonemes (hand-shapes, locations and movements). We evaluated the system on two sign languages -- British SL and Greek SL, both taken from a publicly available corpus, called Dicta Sign Corpus. Achieved average F1 scores are about 95% - indicating that sign languages can be identified with high accuracy using only low-level visual features.

Abstract

We present a vision-based method for signer diarization -- the task of automatically determining "who signed when?" in a video. This task has similar motivations and applications as speaker diarization but has received little attention in the literature. In this paper, we motivate the problem and propose a method for solving it. The method is based on the hypothesis that signers make more movements than their interlocutors. Experiments on four videos (a total of 1.4 hours and each consisting of two signers) show the applicability of the method. The best diarization error rate (DER) obtained is 0.16.

Abstract

This paper presents a Native Language Identification (NLI) system based on TF-IDF weighting schemes and using linear classifiers - support vector machines, logistic regressions and perceptrons. The system was one of the participants of the 2013 NLI Shared Task in the closed-training track, achieving 0.814 overall accuracy for a set of 11 native languages. This accuracy was only 2.2 percentage points lower than the winner's performance. Furthermore, with subsequent evaluations using 10-fold cross-validation (as given by the organizers) on the combined training and development data, the best average accuracy obtained is 0.8455 and the features that contributed to this accuracy are the TF-IDF of the combined unigrams and bigrams of words.

Abstract

We present and solve the speaker diarization problem in a novel way. We hypothesize that the gesturer is the speaker and that identifying the gesturer can be taken as identifying the active speaker. We provide evidence in support of the hypothesis from gesture literature and audio-visual synchrony studies. We also present a vision-only diarization algorithm that relies on gestures (i.e. upper body movements). Experiments carried out on 8.9 hours of a publicly available dataset (the AMI meeting data) show that diarization error rates as low as 15% can be achieved.

Abstract

How are space and time related in the brain? This study contrasts two proposals that make different predictions about the interaction between spatial and temporal magnitudes. Whereas ATOM implies that space and time are symmetrically related, Metaphor Theory claims they are asymmetrically related. Here we investigated whether space and time activate the same neural structures in the inferior parietal cortex (IPC) and whether the activation is symmetric or asymmetric across domains. We measured participants’ neural activity while they made temporal and spatial judgments on the same visual stimuli. The behavioral results replicated earlier observations of a space-time asymmetry: Temporal judgments were more strongly influenced by irrelevant spatial information than vice versa. The BOLD fMRI data indicated that space and time activated overlapping clusters in the IPC and that, consistent with Metaphor Theory, this activation was asymmetric: The shared region of IPC was activated more strongly during temporal judgments than during spatial judgments. We consider three possible interpretations of this neural asymmetry, based on 3 possible functions of IPC.

Abstract

The shape of pitch contours has been shown to have an effect on the perceived duration of vowels. For instance, vowels with high level pitch and vowels with falling contours sound longer than vowels with low level pitch. Depending on whether the
comparison is between level pitches or between level and dynamic contours, these findings have been interpreted in two ways. For inter-level comparisons, where the duration results are the reverse of production results, a hypercorrection strategy in production has been proposed [1]. By contrast, for comparisons between level pitches and dynamic contours, the
longer production data for dynamic contours have been held responsible. We report an experiment with Dutch and Chinese listeners which aimed to show that production data and perception data are each other’s opposites for high, low, falling and rising contours. We explain the results, which are consistent with earlier findings, in terms of the compensatory listening strategy of [2], arguing that the perception effects are due to a perceptual compensation of articulatory strategies and
constraints, rather than that differences in production compensate for psycho-acoustic perception effects.

Abstract

This chapter sketches in very general terms the cognitive architecture of both language comprehension and production, as well as the neurobiological infrastructure that makes the human brain ready for language. Focus is on spoken language, since that compares most directly to processing music. It is worth bearing in mind that humans can also interface with language as a cognitive system using sign and text (visual) as well as Braille (tactile); that is to say, the system can connect with input/output processes in any sensory modality. Language processing consists of a complex and nested set of subroutines to get from sound to meaning (in comprehension) or meaning to sound (in production), with remarkable speed and accuracy. The fi rst section outlines a selection of the major constituent operations, from fractionating the input into manageable units to combining and unifying information in the construction of meaning. The next section addresses the neurobiological infrastructure hypothesized to form the basis for language processing. Principal insights are summarized by building on the notion of “brain networks” for speech–sound processing, syntactic processing, and the construction of meaning, bearing in mind that such a neat three-way subdivision overlooks important overlap and shared mechanisms in the neural architecture subserving language processing. Finally, in keeping with the spirit of the volume, some possible relations are highlighted between language and music that arise from the infrastructure developed here. Our characterization of language and its neurobiological foundations is necessarily selective and brief. Our aim is to identify for the reader critical questions that require an answer to have a plausible cognitive neuroscience of language processing.

Abstract

This paper joins studies of linguistic variation (e.g. Labov 1972; Dubois & Horvath 2000) and discourse (e.g. Jaworski & Lawson 2005; Jaworski & Pritchard 2005; Thurlow & Jaworski 2010) that consider the intersection between language and tourism. By examining the language attitudes that tourists hold toward linguistic variability in their host community, we find that attitudes differ by context and with respect to tourists’ travel motivations. We suggest that these results are particularly likely in a context like Edinburgh, Scotland, where linguistic variation has an iconic link to place authenticity. We propose that the joint commodification of ‘intelligibility’ and ‘authenticity’ explains this variability. The results raise questions about how the commodity value of travel motivation and the associated context of language use influence language attitudes.

Abstract

This paper studies the robustness of exemplar effects in word comprehension by means of four long-term priming experiments with lexical decision tasks in Dutch. A prime and target represented the same word type and were presented with the same or different degree of reduction. In Experiment 1, participants heard only a small number of trials, a large proportion of repeated words, and stimuli produced by only one speaker. They recognized targets more quickly if these represented the same degree of reduction as their primes, which forms additional evidence for the exemplar effects reported in the literature. Similar effects were found for two speakers who differ in their pronunciations. In Experiment 2, with a smaller proportion of repeated words and more trials between prime and target, participants recognized targets preceded by primes with the same or a different degree of reduction equally quickly. Also, in Experiments 3 and 4, in which listeners were not exposed to one but two types of pronunciation variation (reduction degree and speaker voice), no exemplar effects arose. We conclude that the role of exemplars in speech comprehension during natural conversations, which typically involve several speakers and few repeated content words, may be smaller than previously assumed.

Abstract

Faced with planning problems related to lexical access, speakers take advantage of a major function of disfluencies: buying time. It is reasonable, then, to expect that the structure of disfluencies sheds light on the mechanisms underlying lexical access. Using data from the Switchboard Corpus, we investigated the effect of semantic competition during lexical access on repetition disfluencies. We hypothesized that the more time the speaker needs to access the following unit, the longer the repetition. We examined the repetitions preceding verbs and nouns and tested predictors influencing the accessibility of these items. Results suggest that speed of lexical access negatively correlates with the length of repetition and that the main determinants of lexical access speed differ for verbs and nouns. Longer disfluencies before verbs appear to be due to significant paradigmatic competition from semantically similar verbs. For nouns, they occur when the noun is relatively unpredictable given the preceding context.

Abstract

This chapter contains sections titled: Introduction Questions Questioning and the Epistemic Gradient Presuppositions, Agenda Setting and Preferences Social Actions Implemented by Questions Questions as Building Blocks of Institutional Activities Future Directions

Abstract

Three eye-tracking experiments investigated the impact of the complexity of the visual environment on the likelihood of word-object mapping taking place at phonological, semantic and visual levels of representation during language-mediated visual search. Dutch participants heard spoken target words while looking at four objects embedded in displays of different complexity and indicated the presence or absence of the target object. During filler trials the target objects were present, but during experimental trials they were absent and the display contained various competitor objects. For example, given the target word “beaker”, the display contained a phonological (a beaver, bever), a shape (a bobbin, klos), a semantic (a fork, vork) competitor, and an unrelated distractor (an umbrella, paraplu). When objects were presented in simple four-object displays (Experiment 2), there were clear attentional biases to all three types of competitors replicating earlier research (Huettig and McQueen, 2007). When the objects were embedded in complex scenes including four human-like characters or four meaningless visual shapes (Experiments 1, 3), there were biases in looks to visual and semantic but not to phonological competitors. In both experiments, however, we observed evidence for inhibition in looks to phonological competitors, which suggests that the phonological forms of the objects nevertheless had been retrieved. These findings suggest that phonological word-object mapping is contingent upon the nature of the visual environment and add to a growing body of evidence that the nature of our visual surroundings induces particular modes of processing during language-mediated visual search.

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 human face-to-face communication, language comprehension is a multi-modal, situated activity. However, little is known about how we combine information from these different modalities, and how perceived communicative intentions, often signaled through visual signals, such as eye
gaze, may influence this processing. We address this question by simulating a triadic communication context in which a
speaker alternated her gaze between two different recipients. Participants thus viewed speech-only or speech+gesture
object-related utterances when being addressed (direct gaze) or unaddressed (averted gaze). Two object images followed
each message and participants’ task was to choose the object that matched the message. Unaddressed recipients responded significantly slower than addressees for speech-only
utterances. However, perceiving the same speech accompanied by gestures sped them up to a level identical to
that of addressees. That is, when speech processing suffers due to not being addressed, gesture processing remains intact and enhances the comprehension of a speaker’s message

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

Recent experimental evidence from cognitive psychology and cognitive neuroscience shows that reading acquisition has non-trivial consequences for cognitive processes other than reading per se. In the present chapter I present evidence from three areas of cognition: phonological processing, prediction in language processing, and visual search. These findings suggest that literacy on cognition influences are far-reaching. This implies that a good understanding of the dramatic impact of literacy acquisition on the human mind is an important prerequisite for successful education policy development and guidance of educational support.

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

Models of cognitive processes often include simplifications, idealisations, and fictionalisations, so how should we learn about cognitive processes from such models? Particularly in cognitive science, when many features of the target system are unknown, it is not always clear which simplifications, idealisations, and so on, are appropriate for a research question, and which are highly misleading. Here we use a case-study from studies of language evolution, and ideas from philosophy of science, to illustrate a robustness approach to learning from models. Robust properties are those that arise across a range of models, simulations and experiments, and can be used to identify key causal structures in the models, and the phenomenon, under investigation. For example, in studies of language evolution, the emergence of compositional structure is a robust property across models, simulations and experiments of cultural transmission, but only under pressures for learnability and expressivity. This arguably illustrates the principles underlying real cases of language evolution. We provide an outline of the robustness approach, including its limitations, and suggest that this methodology can be productively used throughout cognitive science. Perhaps of most importance, it suggests that different modelling frameworks should be used as tools to identify the abstract properties of a system, rather than being definitive expressions of theories.

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

The human hard palate shows between-subject variation
that is known to influence articulatory strategies.
In order to link such variation to human speech, we
are conducting a cross-sectional MRI study on multiple
populations. A model based on Bezier curves
using only three parameters was fitted to hard palate
MRI tracings using evolutionary computation. The
fits produced consistently yield high accuracies. For
future research, this new method may be used to classify
our MRI data on ethnic origins using e.g., cluster
analyses. Furthermore, we may integrate our model
into three-dimensional representations of the vocal
tract in order to investigate its effect on acoustics and
cultural transmission.

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

The idea that presupposition triggers have different intrinsic properties has gradually made its way into the literature on presuppositions and become a current assumption in most approaches. The distinctions mentioned in the different works have been based on introspective data, which seem, indeed, very suggestive. In this paper, we take a different look at some of these distinctions by using a simple experimental approach based on judgment of naturalness about sentences in various contexts. We show that the alleged difference between weak (or soft) and strong (or hard) triggers is not as clear as one may wish and that the claim that they belong to different lexical classes of triggers is probably much too strong.

Abstract

Second language (L2) research often involves analyses of acoustic measures of fluency. The studies investigating fluency, however, have been difficult to compare because the measures of fluency that were used differed widely. One of the differences between studies concerns the lower cut-off point for silent pauses, which has been set anywhere between 100 ms and 1000 ms. The goal of this paper is to find an optimal cut-off point. We calculate acoustic measures of fluency using different pause thresholds and then relate these measures to a measure of L2 proficiency and to ratings on fluency.

Abstract

Anthropology began by comparing aspects of kinship across cultures, while linguists interested in semantic domains such as kinship necessarily compare across languages. In this chapter I show how phylogenetic comparative methods from evolutionary biology can be used to study evolutionary processes relating to kinship and kinship terminologies across language and culture.

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

Human speakers often produce sentences incrementally. They can start speaking having in mind only a fragmentary idea of what they want to say, and while saying this they refine the contents underlying subsequent parts of the utterance. This capability imposes a number of constraints on the design of a syntactic processor. This paper explores these constraints and evaluates some recent computational sentence generators from the perspective of incremental production.

Abstract

Why do languages have the categories they do? It has been argued that spatial terms in the world’s languages reflect categories that support highly informative communication, and that this accounts for the spatial categories found across languages. However, this proposal has been tested against only nine languages, and in a limited fashion. Here, we consider two new languages: Maijɨki, an under-documented language of Peruvian Amazonia, and English. We analyze spatial data from these two new languages and the original nine, using thorough and theoretically targeted computational tests. The results support the hypothesis that spatial terms across dissimilar languages enable near-optimally informative communication, over an influential competing hypothesis

Abstract

The previous literature has suggested that the hand movement in co-speech gestures and signs consists of a series of phases with qualitatively different dynamic characteristics. In this paper, we propose a syntagmatic rule system for movement phases that applies to both co-speech gestures and signs. Descriptive criteria for the rule system were developed for the analysis video-recorded continuous production of signs and gesture. It involves segmenting a stream of body movement into phases and identifying different phase types. Two human coders used the criteria to analyze signs and cospeech gestures that are produced in natural discourse. It was found that the criteria yielded good inter-coder reliability. These criteria can be used for the technology of automatic recognition of signs and co-speech gestures in order to segment continuous production and identify the potentially meaningbearing phase.

Abstract

Unter allen Disziplinen, die sich mit der Erforschung der Sprache befassen, ist die Lexikografie die älteste und die für die Allgemeinheit wichtigste. Die ältesten, noch sehr einfachen Wörterbücher finden sich auf 4000 Jahre alten Tontafeln, und wenn sich heute in einem Haushalt überhaupt ein Buch findet, dann ist es wahrscheinlich ein Wörterbuch. In den letzten zwanzig Jahren ist die kommerzielle wie die von öffentlich finanzierten Forschungsstätten betriebene Lexikografie jedoch in einer ernsthafte Krise geraten. Die großen Wörterbuchverlage haben die Arbeit an umfassenden Wörterbüchern weitestgehend eingestellt, weil sie kaum noch gekauft werden; die Akademien geraten mit ihren Langzeitvorhaben in massive Zeit- und Finanzprobleme. Wenn wir nicht auf die umfassende Beschreibung des deutschen Wortschatzes in all einer Vielfalt und seiner geschichtlichen Entwicklung verzichten wollen, müssen ganz neue Wege gegangen werden: Wörterbücher im traditionellen Sinne müssen durch digitale lexikalische Systeme ersetzt werden, die das vorhandene lexikalische Wissen integrieren, es schrittweise systematisch ausbauen, eigene Recherchen in verlässlichen Corpora ermöglichen und von jedermann frei über das Internet nutzbar sind.

Abstract

This study investigates the effects of adult age and speaker abilities on articulatory precision for sibilant productions. Normal-hearing young adults with
better sibilant discrimination have been shown to produce greater spectral sibilant contrasts. As reduced auditory feedback may gradually impact on feedforward
commands, we investigate whether articulatory precision as indexed by spectral mean for [s] and [S] decreases with age, and more particularly with agerelated
hearing loss. Younger, middle-aged and older adults read aloud words starting with the sibilants [s] or [S]. Possible effects of cognitive, perceptual, linguistic and sociolinguistic background variables
on the sibilants’ acoustics were also investigated. Sibilant contrasts were less pronounced for male than female speakers. Most importantly, for the fricative
[s], the spectral mean was modulated by individual high-frequency hearing loss, but not age. These results underscore that even mild hearing loss already affects articulatory precision.

Abstract

It is usually assumed that the language spoken by a human community is independent of the community's genetic makeup, an assumption supported by an overwhelming amount of evidence. However, the possibility that language is influenced by its speakers' genes cannot be ruled out a priori, and a recently discovered correlation between the geographic distribution of tone languages and two human genes seems to point to a genetically influenced bias affecting language. This entry describes this specific correlation and highlights its major implications. Voice pitch has a variety of communicative functions. Some of these are probably universal, such as conveying information about the speaker's sex, age, and emotional state. In many languages, including the European languages, voice pitch also conveys certain sentence-level meanings such as signaling that an utterance is a question or an exclamation; these uses of pitch are known as intonation. Some languages, however, known as tone languages, nian ...

Abstract

Speakers of English habitually encode motion events using manner-of-motion verbs (e.g., spin, roll, slide) whereas Spanish speakers rely on path-of-motion verbs (e.g., enter, exit, approach). Here, we ask whether the language-specific verb representations used in encoding motion events induce different modes of “thinking-for-speaking” in Spanish–English bilinguals. That is, assuming that the verb encodes the most salient information in the clause, do bilinguals find the path of motion to be more salient than manner of motion if they had previously described the motion event using Spanish versus English? In our study, Spanish–English bilinguals described a set of target motion events in either English or Spanish and then participated in a nonlinguistic similarity judgment task in which they viewed the target motion events individually (e.g., a ball rolling into a cave) followed by two variants a “same-path” variant such as a ball sliding into a cave or a “same-manner” variant such as a ball rolling away from a cave). Participants had to select one of the two variants that they judged to be more similar to the target event: The event that shared the same path of motion as the target versus the one that shared the same manner of motion. Our findings show that bilingual speakers were more likely to classify two motion events as being similar if they shared the same path of motion and if they had previously described the target motion events in Spanish versus in English. Our study provides further evidence for the “thinking-for-speaking” hypothesis by demonstrating that bilingual speakers can flexibly shift between language-specific construals of the same event “on-the-fly.”

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

Research in body language with use of gesture recognition and speech analysis has gained much attention in the recent times, influencing disciplines related to image and speech processing.

This study aims to design the Media Query Language (MQL) (Lenkiewicz, et al. 2012) combined with the Linguistic Media Query Interface (LMQI) for Elan (Wittenburg, et al. 2006). The system integrated with the new achievements in audio-video recognition will allow querying media files with predefined gesture phases (or motion primitives) and speech characteristics as well as combinations of both. For the purpose of this work the predefined motions and speech characteristics are called patterns for atomic elements and actions for a sequence of patterns. The main assumption is that a user-customized library of patterns and actions and automated media annotation with LMQI will reduce annotation time, hence decreasing costs of creation of annotated corpora. Increase of the number of annotated data should influence the speed and number of possible research in disciplines in which human multimodal interaction is a subject of interest and where annotated corpora are required.

Abstract

The topic of this paper is the way in which speakers order information in discourse. I will refer to this issue with the term "linearization", and will begin with two types of general remarks. The first one concerns the scope and relevance of the problem with reference to some existing literature. The second set of general remarks will be about the place of linearization in a theory of the speaker. The following, and main part of this paper, will be a summary report of research of linearization in a limited, but well-defined domain of discourse, namely the description of spatial networks.