Publications

Abstract

This corpus-based study shows that the presence and duration of schwa in Dutch word-initial syllables are affected by a word’s predictability and its morphological structure. Schwa is less reduced in words that are more predictable given the following word. In addition, schwa may be longer if the syllable forms a prefix, and in prefixes the duration of schwa is positively correlated with the frequency of the word relative to its stem. Our results suggest that the conditions which favor reduced realizations are more complex than one would expect on the basis of the current literature.

Abstract

The Possible-Word Constraint (PWC; Norris, McQueen, Cutler, and Butterfield 1997) suggests that segmentation of continuous speech operates with a universal constraint that feasible words should contain a vowel. Single consonants, because they do not constitute syllables, are treated as non-viable residues. Two word-spotting experiments are reported that investigate whether the PWC really is a language-universal principle. According to the PWC, Slovak listeners should, just like Germans, be slower at spotting words in single consonant contexts (not feasible words) as compared to syllable contexts (feasible words)—even if single consonants can be words in Slovak. The results confirm the PWC in German but not in Slovak.

Abstract

Non-native (L2) speakers of English often experience difficulties in producing English interdental fricatives (e.g. the voiceless [θ]), and this leads to frequent substitutions of these fricatives (e.g. with [t], [s], and [f]). Differences in the choice of [θ]-substitutions across L2 speakers with different native (L1) language backgrounds have been extensively explored. However, even within one foreign accent, more than one substitution choice occurs, but this has been less systematically studied. Furthermore, little is known about whether the substitutions of voiceless [θ] are phonetically clear instances of [t], [s], and [f], as they are often labelled. In this study, we attempted a phonetic approach to examine language-specific preferences for [θ]-substitutions by carrying out acoustic measurements of L1 and L2 realizations of these sounds. To this end, we collected a corpus of spoken English with L1 speakers (UK-English), and Dutch and German L2 speakers. We show a) that the distribution of differential substitutions using identical materials differs between Dutch and German L2 speakers, b) that [t,s,f]-substitutes differ acoustically from intended [t,s,f], and c) that L2 productions of [θ] are acoustically comparable to L1 productions.

Abstract

Certain categories of language learners need feedback on the grammatical structure of sentences they wish to produce. In contrast with the usual NLP approach to this problem—parsing student-generated texts—we propose a generation-based approach aiming at preventing errors (“scaffolding”). In our ICALL system, students construct sentences by composing syntactic trees out of lexically anchored “treelets” via a graphical drag&drop user interface. A natural-language generator computes all possible grammatically well-formed sentences entailed by the student-composed tree, and intervenes immediately when the latter tree does not belong to the set of well-formed alternatives. Feedback is based on comparisons between the student-composed tree and the well-formed set. Frequently occurring errors are handled in terms of “malrules.” The system (implemented in JAVA and C++) currently focuses constituent order in German as L2.

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

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

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

Thesaurus alignment plays an important role in realising efficient access to heterogeneous Cultural Heritage data. Current ontology alignment techniques, however, provide only limited value for such access as they consider little if any requirements from realistic use cases or application scenarios. In this paper, we focus on two real-world scenarios in a library context: thesaurus merging and book re-indexing. We identify their particular requirements and describe our approach of deploying and evaluating thesaurus alignment techniques in this context. We have applied our approach for the Ontology Alignment Evaluation Initiative, and report on the performance evaluation of participants’ tools wrt. the application scenario at hand. It shows that evaluations of tools requires significant effort, but when done carefully, brings many benefits.

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

Most bioacoustics software is used to analyse the already collected acoustics data in batch, i.e., after the data-collecting phase of a scientific study. However, experiments based on animal training require immediate and precise reactions from the experimenter, and thus do not easily dovetail with a typical bioacoustics workflow. Bridging this methodological gap, we have developed a custom application to live-monitor the vocal development of harbour seals in a behavioural experiment. In each trial, the application records and automatically detects an animal's call, and immediately measures duration and acoustic measures such as intensity, fundamental frequency, or formant frequencies. It then displays a spectrogram of the recording and the acoustic measurements, allowing the experimenter to instantly evaluate whether or not to reinforce the animal's vocalisation. From a technical perspective, the rapid and easy development of this custom software was made possible by combining multiple open-source software projects. Here, we integrated the acoustic analyses from Parselmouth, a Python library for Praat, together with PyAudio and Matplotlib's recording and plotting functionality, into a custom graphical user interface created with PyQt. This flexible recombination of different open-source Python libraries allows the whole program to be written in a mere couple of hundred lines of code

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

Kun kuuntelemme puhetta tai luemme tekstiä, alamme välittömästi rakentaa koherenttia tulkintaa. Toisin kuin lukemisessa, puheen havaitsemisessa kuulija voi harvoin kontrolloida nopeutta, jolla hänelle puhutaan. Huolimatta hyvin nopeasta syötteestä - noin 4-7 tavua sekunnissa - ihmiset kykenevät tulkitsemaan puhetta hyvin vaivattomasti. Lauseen ymmärtämisen tutkimuksessa selvitetäänkin, miten tällainen nopea ja useimmiten vaivaton tulkintaprosessi tapahtuu, mitkä kognitiiviset prosessit osallistuvat reaaliaikaiseen tulkintaan ja millaista informaatiota missäkin vaiheessa prosessointia ihminen käyttää hyväkseen johdonmukaisen tulkinnan muodostamiseksi. Tämä kappale on katsaus lauseen ymmärtämisen prosesseihin ja niiden tutkimukseen. Käsittelemme lyhyesti prosessointimalleja, aikuisten ja lasten kielen suhdetta, lauseen sisäisten ja välisten viittaussuhteiden tulkintaa ja sensorisen ympäristön sekä motorisen toiminnan roolia lauseiden tulkintaprosessissa.

Abstract

Adult-to-child interactions are often characterized by prosodically-exaggerated speech accompanied by visually captivating co-speech gestures. In a series of adult studies, we have shown that these gestures are linked in a sophisticated manner to the prosodic structure of adults' utterances. In the current study, we use the Preferential Looking Paradigm to demonstrate that two-year-olds can use the alignment of these gestures to speech to deduce the meaning of words.

Abstract

Speakers express word meaning through systematic but non-canonical acoustic variation of tone of voice (ToV), i.e., variation of speaking rate, pitch, vocal effort, or loudness. Words are, for example, pronounced at a higher pitch when referring to small than to big referents. In the present study, we examined whether listeners can use ToV to learn the meaning of novel adjectives (e.g., “blicket”). During training, participants heard sentences such as “Can you find the blicket one?” spoken with ToV representing hot-cold, strong-weak, and big-small. Participants’ eye movements to two simultaneously shown objects with properties representing the relevant two endpoints (e.g., an elephant and an ant for big-small) were monitored. Assignment of novel adjectives to endpoints was counterbalanced across participants. During test, participants heard the sentences spoken with a neutral ToV, while seeing old or novel picture pairs varying along the same dimensions (e.g., a truck and a car for big-small). Participants had to click on the adjective’s referent. As evident from eye movements, participants did not infer the intended meaning during first exposure, but learned the meaning with the help of ToV during training. At test listeners applied this knowledge to old and novel items even in the absence of informative ToV.

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

This paper compares the focus marking systems and the focus size that can be expressed by the different focus markings in four Mande and three Atlantic languages and varieties, namely: Bambara, Dyula, Kakabe, Soninke (Mande), Wolof, Jóola Foñy and Jóola Karon (Atlantic). All of these languages are known to mark focus morphosyntactically, rather than prosodically, as the more well-studied Germanic languages do. However, the Mande languages under discussion use only morphology, in the form of a particle that follows the focus, while the Atlantic ones use a more complex morphosyntactic system in which focus is marked by morphology in the verbal complex and movement of the focused term. It is shown that while there are some syntactic restrictions to how many different focus sizes can be marked in a distinct way, there is also a certain degree of arbitrariness as to which focus sizes are marked in the same way as each other.

Abstract

Sign language is a rich form of communication, uniquely conveying meaning through a combination of gestures, facial expressions, and body movements. Existing research in sign language generation has predominantly focused on text-to-sign pose generation, while speech-to-sign pose generation remains relatively underexplored. Speech-to-sign language generation models can facilitate effective communication between the deaf and hearing communities. In this paper, we propose an architecture that utilises prosodic information from speech audio and semantic context from text to generate sign pose sequences. In our approach, we adopt a multi-tasking strategy that involves an additional task of predicting Facial Action Units (FAUs). FAUs capture the intricate facial muscle movements that play a crucial role in conveying specific facial expressions during sign language generation. We train our models on an existing Indian Sign language dataset that contains sign language videos with audio and text translations. To evaluate our models, we report Dynamic Time Warping (DTW) and Probability of Correct Keypoints (PCK) scores. We find that combining prosody and text as input, along with incorporating facial action unit prediction as an additional task, outperforms previous models in both DTW and PCK scores. We also discuss the challenges and limitations of speech-to-sign pose generation models to encourage future research in this domain. We release our models, results and code to foster reproducibility and encourage future research1.

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

We present an overview of several corpus studies we carried out into the frequencies of argument NP orderings in the midfield of subordinate and main clauses of German. Comparing the corpus frequencies with grammaticality ratings published by Keller’s (2000), we observe a “grammaticality–frequency gap”: Quite a few argument orderings with zero corpus frequency are nevertheless assigned medium–range grammaticality ratings. We propose an explanation in terms of a two-factor theory. First, we hypothesize that the grammatical induction component needs a sufficient number of exposures to a syntactic pattern to incorporate it into its repertoire of more or less stable rules of grammar. Moderately to highly frequent argument NP orderings are likely have attained this status, but not their zero-frequency counterparts. This is why the latter argument sequences cannot be produced by the grammatical encoder and are absent from the corpora. Secondly, we assumed that an extraneous (nonlinguistic) judgment process biases the ratings of moderately grammatical linear order patterns: Confronted with such structures, the informants produce their own “ideal delivery” variant of the to-be-rated target sentence and evaluate the similarity between the two versions. A high similarity score yielded by this judgment then exerts a positive bias on the grammaticality rating—a score that should not be mistaken for an authentic grammaticality rating. We conclude that, at least in the linearization domain studied here, the goal of gaining a clear view of the internal grammar of language users is best served by a combined strategy in which grammar rules are founded on structures that elicit moderate to high grammaticality ratings and attain at least moderate usage frequencies.

Abstract

The ”download first, then process paradigm” is still the predominant working method amongst the research community. The web-based paradigm, however, offers many advantages from a tool development and data management perspective as they allow a quick adaptation to changing research environments. Moreover, new ways of combining tools and data are increasingly becoming available and will eventually enable a true web-based workflow approach, thus challenging the ”download first, then process” paradigm. The necessary infrastructure for managing, exploring and enriching language resources via the Web will need to be delivered by projects like CLARIN and DARIAH

Abstract

In this paper, we describe a unifying approach to tackle data heterogeneity issues for lexica and related resources. We present LEXUS, our software that implements the Lexical Markup Framework (LMF) to uniformly describe and manage lexica of different structures. LEXUS also makes use of a central Data Category Registry (DCR) to address terminological issues with regard to linguistic concepts as well as the handling of working and object languages. Finally, we report on ViCoS, a LEXUS extension, providing support for the definition of arbitrary semantic relations between lexical entries or parts thereof.

Abstract

To achieve true interoperability for valuable linguistic resources different levels of variation need to be addressed. ISO Technical Committee 37, Terminology and other language and content resources, is developing a Data Category Registry. This registry will provide a reusable set of data categories. A new implementation, dubbed ISOcat, of the registry is currently under construction. This paper shortly describes the new data model for data categories that will be introduced in this implementation. It goes on with a sketch of the standardization process. Completed data categories can be reused by the community. This is done by either making a selection of data categories using the ISOcat web interface, or by other tools which interact with the ISOcat system using one of its various Application Programming Interfaces. Linguistic resources that use data categories from the registry should include persistent references, e.g. in the metadata or schemata of the resource, which point back to their origin. These data category references can then be used to determine if two or more resources share common semantics, thus providing a level of interoperability close to the source data and a promising layer for semantic alignment on higher levels

Abstract

We present a software module, the LAT Bridge, which enables bidirectionalcommunication between the annotation and exploration tools developed at the MaxPlanck Institute for Psycholinguistics as part of our Language ArchivingTechnology (LAT) tool suite. These existing annotation and exploration toolsenable the annotation, enrichment, exploration and archive management oflinguistic resources. The user community has expressed the desire to usedifferent combinations of LAT tools in conjunction with each other. The LATBridge is designed to cater for a number of basic data interaction scenariosbetween the LAT annotation and exploration tools. These interaction scenarios(e.g. bootstrapping a wordlist, searching for annotation examples or lexicalentries) have been identified in collaboration with researchers at ourinstitute.We had to take into account that the LAT tools for annotation and explorationrepresent a heterogeneous application scenario with desktop-installed andweb-based tools. Additionally, the LAT Bridge has to work in situations wherethe Internet is not available or only in an unreliable manner (i.e. with a slowconnection or with frequent interruptions). As a result, the LAT Bridge’sarchitecture supports both online and offline communication between the LATannotation and exploration tools.

Abstract

Many theories hold that semantic variation in the world’s languages can be explained in terms of a universal conceptual space that is partitioned differently by different languages. Recent work has supported this view in the semantic domain of containers (Malt et al., 1999), and assumed it in the domain of spatial relations (Khetarpal et al., 2009), based in both cases on similarity judgments derived from pile-sorting of stimuli. Here, we reanalyze data from these two studies and find a more complex picture than these earlier studies suggested. In both cases we find that sorting is similar across speakers of different languages (in line with the earlier studies), but nonetheless reflects the sorter’s native language (in contrast with the earlier studies). We conclude that there are cross-culturally shared conceptual tendencies that can be revealed by pile-sorting, but that these tendencies may be modulated to some extent by language. We discuss the implications of these findings for accounts of semantic variation.

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

No area in the study of human languages has a longer history and a higher practical signifi cance than lexicography. The advent of the computer has dramaticually changed this discipline in ways which go far beyond the digitisation of materials in combination with effi cient search tools, or the transfer of an existing dictionary onto the computer. They allow the stepwise elaboration of what is called here Digital Lexical Systems, i.e., computerized systems in which the underlying data - in form of an extendable corpus - and description of lexical properties on various levels can be effi ciently combined. This paper discusses the range of these possibilities and describes the present form of the German „Digital Lexical System of the Academy“, a project of the Berlin-Brandenburg Academy of Sciences (www.dwds.de).

Abstract

Previous studies on Cantonese Chinese showed that rising
question intonation contours on low-toned words lead to
frequent misperceptions of the tones. Here we explored the
processing consequences of this interaction between tone and
intonation by comparing the processing and identification of
monosyllabic critical words at the end of questions and
statements, using a tone identification task, and ERPs as an
online measure of speech comprehension. Experiment 1
yielded higher error rates for the identification of low tones at
the end of questions and a larger N400-P600 pattern, reflecting
processing difficulty and reanalysis, compared to other
conditions. In Experiment 2, we investigated the effect of
immediate lexical context on the tone by intonation interaction.
Increasing contextual constraints led to a reduction in errors
and the disappearance of the P600 effect. These results
indicate that there is an immediate interaction between tone,
intonation, and context in online speech comprehension. The
difference in performance and activation patterns between the
two experiments highlights the significance of context in
understanding a tone language, like Cantonese-Chinese.

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

Interpreting the meaning of co-speech gesture often involves
identifying a gesture’s ‘lexical affiliate’, the word or phrase to
which it most closely relates (Schegloff 1984). Though there is
work within gesture studies that resists this simplex mapping of
meaning from speech to gesture (e.g. de Ruiter 2000; Kendon
2014; Parrill 2008), including an evolving body of literature on
recurrent gesture and gesture families (e.g. Fricke et al. 2014; Müller 2017), it is still the lexical affiliate model that is most ap-
parent in formal linguistic models of multimodal meaning(e.g.
Alahverdzhieva et al. 2017; Lascarides and Stone 2009; Puste-
jovsky and Krishnaswamy 2021; Schlenker 2020). In this work,
I argue that the lexical affiliate should be carefully reconsidered
in the further development of such models.
In place of the lexical affiliate, I suggest a further shift
toward a frame-based, action schematic approach to gestural
meaning in line with that proposed in, for example, Parrill and
Sweetser (2004) and Müller (2017). To demonstrate the utility
of this approach I present three types of compositional gesture
sequences which I call spatial contrast, spatial embedding, and
cooperative abstract deixis. All three rely on gestural context,
rather than gesture-speech alignment, to convey interactive (i.e.
pragmatic) meaning. The centrality of gestural context to ges-
ture meaning in these examples demonstrates the necessity of
developing a model of gestural meaning independent of its in-
tegration with speech.

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

Digital processing of medical images has helped physicians and patients during past years by allowing examination and diagnosis on a very precise level. Nowadays possibly the biggest deal of support it can offer for modern healthcare is the use of high performance computing architectures to treat the huge amounts of data that can be collected by modern acquisition devices. This paper presents a parallel processing implementation of an image segmentation algorithm that operates on a computer cluster equipped with 10 processing units. Thanks to well-organized distribution of the workload we manage to significantly shorten the execution time of the developed algorithm and reach a performance gain very close to linear.

Abstract

Since the core matrix for language use is interaction, the main job of language
is not to express propositions or abstract meanings, but to deliver actions.
For in order to respond in interaction we have to ascribe to the prior turn
a primary ‘action’ – variously thought of as an ‘illocution’, ‘speech act’, ‘move’,
etc. – to which we then respond. The analysis of interaction also relies heavily
on attributing actions to turns, so that, e.g., sequences can be characterized in
terms of actions and responses. Yet the process of action ascription remains way
understudied. We don’t know much about how it is done, when it is done, nor even
what kind of inventory of possible actions might exist, or the degree to which they
are culturally variable.
The study of action ascription remains perhaps the primary unfulfilled task in
the study of language use, and it needs to be tackled from conversationanalytic,
psycholinguistic, cross-linguistic and anthropological perspectives.
In this talk I try to take stock of what we know, and derive a set of goals for and
constraints on an adequate theory. Such a theory is likely to employ, I will suggest,
a top-down plus bottom-up account of action perception, and a multi-level notion
of action which may resolve some of the puzzles that have repeatedly arisen.

Abstract

Given the diversity of languages, it is unlikely that the human capacity for language resides in rich universal syntactic machinery. More likely, it resides centrally in the capacity for vocal learning combined with a distinctive ethology for communicative interaction, which together (no doubt with other capacities) make diverse languages learnable. This chapter focuses on face-to-face communication, which is characterized by the mapping of sounds and multimodal signals onto speech acts and which can be deeply recursively embedded in interaction structure, suggesting an interactive origin for complex syntax. These actions are recognized through Gricean intention recognition, which is a kind of “ mirroring” or simulation distinct from the classic mirror neuron system. The multimodality of conversational interaction makes evident the involvement of body, hand, and mouth, where the burden on these can be shifted, as in the use of speech and gesture, or hands and face in sign languages. Such shifts having taken place during the course of human evolution. All this suggests a slightly different approach to the mystery of music, whose origins should also be sought in joint action, albeit with a shift from turn-taking to simultaneous expression, and with an affective quality that may tap ancient sources residual in primate vocalization. The deep connection of language to music can best be seen in the only universal form of music, namely song.