Publications

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

In different fields of the humanities annotations of multimodal resources are a necessary component of the research workflow. Examples include linguistics, psychology, anthropology, etc. However, creation of those annotations is a very laborious task, which can take 50 to 100 times the length of the annotated media, or more. This can be significantly improved by applying innovative audio and video processing algorithms, which analyze the recordings and provide automated annotations. This is the aim of the AVATecH project, which is a collaboration of the Max Planck Institute for Psycholinguistics (MPI) and the Fraunhofer institutes HHI and IAIS. In this paper we present a set of results of automated annotation together with an evaluation of their quality.

Abstract

Introduction Human spoken communication is multimodal, i.e. it encompasses both speech and gesture. Acoustic properties of voice, body movements, facial expression, etc. are an inherent and meaningful part of spoken interaction; they can provide attitudinal, grammatical and semantic information. In the recent years interest in audio-visual corpora has been rising rapidly as they enable investigation of different communicative modalities and provide more holistic view on communication (Kipp et al. 2009). Moreover, for some languages such corpora are the only available resource, as is the case for endangered languages for which no written resources exist.

Abstract

In this paper we describe audio and video processing algorithms that are developed in the scope of AVATecH project. The purpose of these algorithms is to shorten the time taken by manual annotation of audio and video recordings by extracting features from media files and creating semi-automated annotations. We show that the use of such supporting algorithms can shorten the annotation time to 30-50% of the time necessary to perform a fully manual annotation of the same kind.

Abstract

Presentation of the official opening of the Jerome Bruner Library, January 8th, 2020

Abstract

This paper describes the linguistic treatment of placement events in the Rossel Island (Papua New Guinea) language Yélî Dnye. Yélî Dnye is unusual in treating PUT and TAKE events symmetrically with a remarkable consistency. In what follows, we first provide a brief background for the language, then describe the six core PUT/TAKE verbs that were drawn upon by Yélî Dnye speakers to describe the great majority of the PUT/TAKE stimuli clips, along with some of their grammatical properties. In Section 5 we describe alternative verbs usable in particular circumstances and give an indication of the basis for variability in responses across speakers. Section 6 presents some reasons why the Yélî verb pattern for expressing PUT and TAKE events is of broad interest.

Abstract

Languages differ in the degree of semantic flexibility of their syntactic roles. For example, Eng-
lish and Indonesian are considered more flexible with regard to the semantics of subjects,
whereas German and Japanese are less flexible. In Hawkins’ classification, more flexible lan-
guages are said to have a loose fit, and less flexible ones are those that have a tight fit. This
classification has been based on manual inspection of example sentences. The present paper
proposes a new, quantitative approach to deriving the measures of looseness and tightness from
corpora. We use corpora of online news from the Leipzig Corpora Collection in thirty typolog-
ically and genealogically diverse languages and parse them syntactically with the help of the
Universal Dependencies annotation software. Next, we compute Mutual Information scores for
each language using the matrices of lexical lemmas and four syntactic dependencies (intransi-
tive subjects, transitive subject, objects and obliques). The new approach allows us not only to
reproduce the results of previous investigations, but also to extend the typology to new lan-
guages. We also demonstrate that verb-final languages tend to have a tighter relationship be-
tween lexemes and syntactic roles, which helps language users to recognize thematic roles early
during comprehension.

Abstract

We present the Narrative Brain Dataset, an fMRI dataset that was collected during spoken presentation of short excerpts of three
stories in Dutch. Together with the brain imaging data, the dataset contains the written versions of the stimulation texts. The texts are
accompanied with stochastic (perplexity and entropy) and semantic computational linguistic measures. The richness and unconstrained
nature of the data allows the study of language processing in the brain in a more naturalistic setting than is common for fMRI studies.
We hope that by making NBD available we serve the double purpose of providing useful neural data to researchers interested in natural
language processing in the brain and to further stimulate data sharing in the field of neuroscience of language.

Abstract

Children learn language from the speech in their home environment. Recent work shows that more infant-directed speech
(IDS) leads to stronger lexical development. But what makes IDS a particularly useful learning signal? Here, we expand on an attention-based account first proposed by Räsänen et al. (2018): that prosodic modifications make IDS less predictable, and thus more interesting. First, we reproduce the critical finding from Räsänen et al.: that lab-recorded IDS pitch is less predictable compared to adult-directed speech (ADS). Next, we show that this result generalizes to the home language environment, finding that IDS in daylong recordings is also less predictable than ADS but that this pattern is much less robust than for IDS recorded in the lab. These results link experimental work on attention and prosodic modifications of IDS to real-world language-learning environments, highlighting some challenges of scaling up analyses of IDS to larger datasets that better capture children’s actual input.

Abstract

For (semi-)automated subject indexing systems in digital libraries, it is often more practical to use metadata such as the title of a publication instead of the full-text or the abstract. Therefore, it is desirable to have good text mining and text classification algorithms that operate well already on the title of a publication. So far, the classification performance on titles is not competitive with the performance on the full-texts if the same number of training samples is used for training. However, it is much easier to obtain title data in large quantities and to use it for training than full-text data. In this paper, we investigate the question how models obtained from training on increasing amounts of title training data compare to models from training on a constant number of full-texts. We evaluate this question on a large-scale dataset from the medical domain (PubMed) and from economics (EconBiz). In these datasets, the titles and annotations of millions of publications are available, and they outnumber the available full-texts by a factor of 20 and 15, respectively. To exploit these large amounts of data to their full potential, we develop three strong deep learning classifiers and evaluate their performance on the two datasets. The results are promising. On the EconBiz dataset, all three classifiers outperform their full-text counterparts by a large margin. The best title-based classifier outperforms the best full-text method by 9.4%. On the PubMed dataset, the best title-based method almost reaches the performance of the best full-text classifier, with a difference of only 2.9%.

Abstract

Lexical stress is realised similarly in English, German, and
Dutch. On a suprasegmental level, stressed syllables tend to be
longer and more acoustically salient than unstressed syllables;
segmentally, vowels in unstressed syllables are often reduced.
The frequency of unreduced unstressed syllables (where only
the suprasegmental cues indicate lack of stress) however,
differs across the languages. The present studies test whether
listener behaviour is affected by these vocabulary differences,
by investigating German listeners’ use of suprasegmental cues
to lexical stress in German and English word recognition. In a
forced-choice identification task, German listeners correctly
assigned single-syllable fragments (e.g., Kon-) to one of two
words differing in stress (KONto, konZEPT). Thus, German
listeners can exploit suprasegmental information for
identifying words. German listeners also performed above
chance in a similar task in English (with, e.g., DIver, diVERT),
i.e., their sensitivity to these cues also transferred to a nonnative
language. An English listener group, in contrast, failed
in the English fragment task. These findings mirror vocabulary
patterns: German has more words with unreduced unstressed
syllables than English does.

Abstract

What is the relationship between the language we speak and the way we think? Researchers working at the interface of language and cognition hope to understand the complex interplay between linguistic structures and the way the mind works. This is thorny territory in anthropology and its closely allied disciplines, such as linguistics and psychology.

Abstract

Scholars disagree about the extent to which language can tell us
about conceptualisation of the world. Some believe that language
is a direct window onto concepts: Having a word ‘‘bird’’, ‘‘table’’ or
‘‘sour’’ presupposes the corresponding underlying concept, BIRD,
TABLE, SOUR. Others disagree. Words are thought to be uninformative,
or worse, misleading about our underlying conceptual representations;
after all, our mental worlds are full of ideas that we
struggle to express in language. How could this be so, argue sceptics,
if language were a direct window on our inner life? In this presentation,
I consider what language can tell us about the
conceptualisation of taste. By considering linguistic data from
twenty unrelated cultures – varying in subsistence mode (huntergatherer
to industrial), ecological zone (rainforest jungle to desert),
dwelling type (rural and urban), and so forth – I argue any single language is, indeed, impoverished about what it can reveal about
taste. But recurrent lexicalisation patterns across languages can
provide valuable insights about human taste experience. Moreover,
language patterning is part of the data that a good theory of taste
perception has to be answerable for. Taste researchers, therefore,
cannot ignore the crosslinguistic facts.

Abstract

La ciencia moderna nace de la conjunción entre postulados teóricos y el desarrollo de una infraestructura tecnológica que permite observar los hechos de manera adecuada, realizar experimentos y verificar las hipótesis. Desde Galileo, ciencia y tecnología han avanzado conjuntamente. En el mundo occidental, la ciencia ha evolucionado desde pro-puestas puramente especulativas (basadas en postulados apriorísticos) hasta el uso de métodos experimentales y estadísticos para explicar mejor nuestras observaciones. La tecnología se hermana con la ciencia facilitando al investigador una aproximación adecuada a los hechos que pretende explicar. Así, Galileo, para observar los cuerpos celestes, mejoró el utillaje óptico, lo que le permitió un acercamiento más preciso al objeto de estudio y, en consecuencia, unos fundamentos más sólidos para su propuesta teórica. De modo similar, actualmente el desarrollo tecnológico digital ha posibilitado la extracción masiva de datos y el análisis estadístico de éstos para verificar las hipótesis de partida: la lingüística no ha podido dar el paso desde la pura especulación hacia el análisis estadístico de los hechos hasta la aparición de las tecnologías digitales.

Abstract

Grice in pragmatics and Levelt in psycholinguistics have proposed models of human communication where the starting point of communicative action is an individual intention. This assumption, though, has to face serious objections with regard to the alleged existence of explicit representations of the communicative goals to be pursued. Here evidence is surveyed which shows that in fact speaking may ordinarily be a quite automatic activity prompted by contextual cues and driven by behavioural schemata abstracted away from social regularities. On the one hand, this means that there could exist no intentions in the sense of explicit representations of communicative goals, following from deliberate reasoning and triggering the communicative action. On the other hand, however, there are reasons to allow for a weaker notion of intention than this, according to which communication is an intentional affair, after all. Communicative action is said to be intentional in this weaker sense to the extent that it is subject to a double mechanism of control, with respect both to present-directed and future-directed intentions.

Abstract

This chapter outlines a Bayesian model of spoken-word recognition and reviews how
prosody is part of that model. The review focuses on the information that assists the lis­
tener in recognizing the prosodic structure of an utterance and on how spoken-word
recognition is also constrained by prior knowledge about prosodic structure. Recognition
is argued to be a process of perceptual inference that ensures that listening is robust to
variability in the speech signal. In essence, the listener makes inferences about the seg­
mental content of each utterance, about its prosodic structure (simultaneously at differ­
ent levels in the prosodic hierarchy), and about the words it contains, and uses these in­
ferences to form an utterance interpretation. Four characteristics of the proposed
prosody-enriched recognition model are discussed: parallel uptake of different informa­
tion types, high contextual dependency, adaptive processing, and phonological abstrac­
tion. The next steps that should be taken to develop the model are also discussed.

Abstract

The results of a word-spotting experiment are presented in which Dutch listeners tried to spot different types of bisyllabic Dutch words embedded in different types of nonsense contexts. Embedded verbs were not reliably harder to spot than embedded nouns; this suggests that nouns and verbs are recognised via the same basic processes. Iambic words were no harder to spot than trochaic words, suggesting that trochaic words are not in principle easier to recognise than iambic words. Words were harder to spot in consonantal contexts (i.e., contexts which themselves could not be words) than in longer contexts which contained at least one vowel (i.e., contexts which, though not words, were possible words of Dutch). A control experiment showed that this difference was not due to acoustic differences between the words in each context. The results support the claim that spoken-word recognition is sensitive to the viability of sound sequences as possible words.

Abstract

The ultimate goal of our research is to improve an existing speech-based computational model of human speech recognition on the task of simulating the role of fine-grained phonetic information in human speech processing. As part of this work we are investigating articulatory feature classifiers that are able to create reliable and accurate transcriptions of the articulatory behaviour encoded in the acoustic speech signal. Articulatory feature (AF) modelling of speech has received a considerable amount of attention in automatic speech recognition research. Different approaches have been used to build AF classifiers, most notably multi-layer perceptrons. Recently, deep neural networks have been applied to the task of AF classification. This paper aims to improve AF classification by investigating two different approaches: 1) investigating the usefulness of a deep Convolutional neural network (CNN) for AF classification; 2) integrating the Mel filtering operation into the CNN architecture. The results showed a remarkable improvement in classification accuracy of the CNNs over state-of-the-art AF classification results for Dutch, most notably in the minority classes. Integrating the Mel filtering operation into the CNN architecture did not further improve classification performance.

Abstract

Analyzing EEG signals recorded while participants are listening to continuous speech with the purpose of testing linguistic hypotheses is complicated by the fact that the signals simultaneously reflect exogenous acoustic excitation and endogenous linguistic processing. This makes it difficult to trace subtle differences that occur in mid-sentence position. We apply an analysis based on multivariate temporal response functions to uncover subtle mid-sentence effects. This approach is based on a per-stimulus estimate of the response of the neural system to speech input. Analyzing EEG signals predicted on the basis of the response functions might then bring to light conditionspecific differences in the filtered signals. We validate this approach by means of an analysis of EEG signals recorded with isolated word stimuli. Then, we apply the validated method to the analysis of the responses to the same words in the middle of meaningful sentences.

Abstract

Studies have shown that listeners segmenting unfamiliar languages transfer native-language (L1) segmentation cues. These studies, however, conflated L1 and recent linguistic exposure. The present study investigates the relative influences of L1 and recent linguistic exposure on the use of prosodic cues for segmenting an artificial language (AL). Participants were L1-French listeners, high-proficiency L2-French L1-English listeners, and L1-English listeners without functional knowledge of French. The prosodic cue assessed was F0 rise, which is word-final in French, but in English tends to be word-initial. 30 participants heard a 20-minute AL speech stream with word-final boundaries marked by F0 rise, and decided in a subsequent listening task which of two words (without word-final F0 rise) had been heard in the speech stream. The analyses revealed a marginally significant effect of L1 (all listeners) and, importantly, a significant effect of recent linguistic exposure (L1-French and L2-French listeners): accuracy increased with decreasing time in the US since the listeners’ last significant (3+ months) stay in a French-speaking environment. Interestingly, no effect of L2 proficiency was found (L2-French listeners).

Abstract

Many languages have general or “light” verbs used by speakers to describe a wide range of situations owing to their relatively schematic meanings, e.g., the English verb do that can be used to describe many different kinds of actions, or the verb put that labels a range of types of placement of objects at locations. Such semantically bleached verbs often become grammaticalized and used to encode an extended (set of) meaning(s), e.g., Tamil veyyii ‘put/place’ is used to encode causative meaning in periphrastic causatives (e.g., okkara veyyii ‘make sit’, nikka veyyii ‘make stand’). But do general verbs in different languages have the same kinds of (schematic) meanings and extensional ranges? Or do they reveal different, perhaps even cross-cutting, ways of structuring the same semantic domain in different languages? These questions require detailed crosslinguistic investigation using comparable methods of eliciting data. The present study is a first step in this direction, and focuses on the use of general verbs to describe events of placement and removal in two South Asian languages, Hindi and Tamil.

Abstract

The human language processor is conceived as a system that consists of several interrelated subsystems. Each subsystem performs a specific task in the complex process of language comprehension and production. A subsystem receives a particular input, performs certain specific operations on this input and yields a particular output. The subsystems can be characterized in terms of the transformations that relate the input representations to the output representations. An important issue in describing the language processing system is to identify the subsystems and to specify the relations between the subsystems. These relations can be conceived in two different ways. In one conception the subsystems are autonomous. They are related to each other only by the input-output channels. The operations in one subsystem are not affected by another system. The subsystems are modular, that is they are independent. In the other conception, the different subsystems influence each other. A subsystem affects the processes in another subsystem. In this conception there is an interaction between the subsystems.

Abstract

Egophoric verbal marking is a typological feature common to Barbacoan languages, but otherwise unknown in the Andean sphere. The verbal systems of three out of the four living Barbacoan languages, Cha’palaa, Tsafiki and Awa Pit, have previously been shown to express egophoric contrasts. The status of Guambiano has, however, remained uncertain. In this chapter, I show that there are in fact two layers of egophoric or egophoric-like marking visible in Guambiano’s grammar. Guambiano patterns with certain other (non-Barbacoan) languages in having ego-categories which function within a broader evidential system. It is additionally possible to detect what is possibly a more archaic layer of egophoric marking in Guambiano’s verbal system. This marking may be inherited from a common Barbacoan system, thus pointing to a potential genealogical basis for the egophoric patterning common to these languages. The multiple formal expressions of egophoricity apparent both within and across the four languages reveal how egophoric contrasts are susceptible to structural renewal, suggesting a pan-Barbacoan preoccupation with the linguistic encoding of self-knowledge.

Abstract

Language resources can be divided into structural resources treating phonology, morphosyntax, semantics etc. and resources treating the social, demographic, ethnic, political context. A third type are meta-resources, like bibliographies, which provide access to the resources of the first two kinds. This poster will present the Glottolog/Langdoc project, a comprehensive bibliography providing web access to 180k bibliographical records to (mainly) low visibility resources from low-density languages. The resources are annotated for macro-area, content language, and document type and are available in XHTML and RDF.

Abstract

This article explores the expression of placement and removal events in Moroccan Arabic, particularly the semantic features of ‘putting’ and ‘taking’ verbs, classified in accordance with their combination with Goal and/or Source NPs. Moroccan Arabic verbs encode a variety of components of placement and removal events, including containment, attachment, features of the figure, and trajectory. Furthermore, accidental events are distinguished from deliberate events either by the inherent semantics of predicates or denoted syntactically. The postures of the Figures, in spite of some predicates distinguishing them, are typically not specified as they are in other languages, such as Dutch. Although Ground locations are frequently mentioned in both source-oriented and goal-oriented clauses, they are used more often in goal-oriented clauses.

Abstract

This paper offers a structural and semantic analysis of expressions of caused motion in Lowland Chontal of Oaxaca, an indigenous language of southern Mexico. The data were collected using a video stimulus designed to elicit a wide range of caused motion event descriptions. The most frequent event types in the corpus depict caused motion to and from relations of support and containment, fundamental notions in the de­scription of spatial relations between two entities and critical semantic components of the linguistic encoding of caused motion in this language. Formal features of verbal construction type and argument realization are examined by sorting event descriptions into semantic types of placement and removal, to and from support and to and from containment. Together with typological factors that shape the distribution of spatial semantics and referent expression, separate treatments of support and containment relations serve to clarify notable asymmetries in patterns of predicate type and argument realization.

Abstract

Japanese listeners detected Japanese words embedded at the end of nonsense sequences (e.g., kaba 'hippopotamus' in gyachikaba). When the final portion of the preceding context together with the initial portion of the word (e.g., here, the sequence chika) was compatible with many lexical competitors, recognition of the embedded word was more difficult than when such a sequence was compatible with few competitors. This clear effect of competition, established here for preceding context in Japanese, joins similar demonstrations, in other languages and for following contexts, to underline that the functional architecture of the human spoken-word recognition system is a universal one.

Abstract

Our ability to use language is multimodal and requires tight coordination between what is expressed in speech and in gesture, such as pointing or iconic gestures that convey semantic, syntactic and pragmatic information related to speakers’ messages. Interestingly, what is expressed in gesture and how it is coordinated with speech differs in speakers of different languages. This paper discusses recent findings on the development of children’s multimodal expressions taking cross-linguistic variation into account. Although some aspects of speech-gesture development show language-specificity from an early age, it might still take children until nine years of age to exhibit fully adult patterns of cross-linguistic variation. These findings reveal insights about how children coordinate different levels of representations given that their development is constrained by patterns that are specific to their languages.

Abstract

Gestures are meaningful movements of the body, the hands, and the face during communication,
which accompany the production of both spoken and signed utterances. Recent
research has shown that gestures are an integral part of language and that they contribute
semantic, syntactic, and pragmatic information to the linguistic utterance. Furthermore,
they reveal internal representations of the language user during communication in ways
that might not be encoded in the verbal part of the utterance. Firstly, this chapter summarizes
research on the role of gesture in spoken languages. Subsequently, it gives an overview
of how gestural components might manifest themselves in sign languages, that is,
in a situation in which both gesture and sign are expressed by the same articulators.
Current studies are discussed that address the question of whether gestural components are the same or different in the two language modalities from a semiotic as well as from a cognitive and processing viewpoint. Understanding the role of gesture in both sign and
spoken language contributes to our knowledge of the human language faculty as a multimodal communication system.

Abstract

Use of language in face-to-face context is multimodal. Production and perception of speech take place in the context of visual articulators such as lips, face, or hand gestures which convey relevant information to what is expressed in speech at different levels of language. While lips convey information at the phonological level, gestures contribute to semantic, pragmatic, and syntactic information, as well as to discourse cohesion. This chapter overviews recent findings showing that speech and gesture (e.g. a drinking gesture as someone says, “Would you like a drink?”) interact during production and comprehension of language at the behavioral, cognitive, and neural levels. Implications of these findings for current psycholinguistic theories and how they can be expanded to consider the multimodal context of language processing are discussed.

Abstract

Automating robot behavior in a specific situation is an active area of research. There are several approaches available in the literature of robotics to cater for the automatic behavior of a robot. However, when it comes to humanoids or human-robot interaction in general, the area has been less explored. In this paper, a pseudo-randomization approach has been introduced to automatize the gestures and facial expressions of an interactive humanoid robot called ROBIN based on its mental state. A significant number of gestures and facial expressions have been implemented to allow the robot more options to perform a relevant action or reaction based on visual stimuli. There is a display of noticeable differences in the behaviour of the robot for the same stimuli perceived from an interaction partner. This slight autonomous behavioural change in the robot clearly shows a notion of automation in behaviour. The results from experimental scenarios and human-centered evaluation of the system help validate the approach.

Abstract

Wanneer iemand goed is in het spreken van meerdere talen, wordt wel gezegd dat zo iemand een talenknobbel heeft. Iedereen weet dat dat niet letterlijk bedoeld is: iemand met een talenknobbel herkennen we niet aan een grote bult op zijn hoofd. Toch dacht men vroeger wel degelijk dat mensen een letterlijke talenknobbel konden ontwikkelen. Een goed ontwikkeld taalvermogen zou gepaard gaan met het groeien van het hersengebied dat hiervoor verantwoordelijk was. Dit deel van het brein zou zelfs zo groot kunnen worden dat het van binnenuit tegen de schedel drukte, met name rond de ogen. Nu weten we wel beter. Maar waar in het brein bevindt de taal zich dan wel precies?

Abstract

This chapter focuses on the semantic and pragmatic uses of space. The questions addressed concern how sign space (i.e. the area of space in front of the signer’s body) is used for meaning construction, how locations in sign space are associated with discourse referents, and how signers choose to structure sign space for their communicative intents. The chapter gives an overview of linguistic analyses of the use of space, starting with the distinction between syntactic and topographic uses of space and the different types of signs that function to establish referent-location associations, and moving to analyses based on mental spaces and conceptual blending theories. Semantic-pragmatic conventions for organizing sign space are discussed, as well as spatial devices notable in the visual-spatial modality (particularly, classifier predicates and signing perspective), which influence and determine the way meaning is created in sign space. Finally, the special role of simultaneity in sign languages is discussed, focusing on the semantic and discourse-pragmatic functions of simultaneous constructions.

Abstract

In Kalasha, an Indo-Aryan language spoken in Northwest Pakistan, the linguistic encoding of ‘put’ and ‘take’ events reveals a symmetry between lexical ‘put’ and ‘take’ verbs that implies ‘placement on’ and ‘removal from’ a supporting surface. As regards ‘placement in’ and ‘removal from’ an enclosure, the data reveal a lexical asymmetry as ‘take’ verbs display a larger degree of linguistic elaboration of the Figure-Ground relation and the type of caused motion than ‘put’ verbs. When considering syntactic patterns, more instances of asymmetry between these two event types show up. The analysis presented here supports the proposal that an asymmetry exists in the encoding of goals versus sources as suggested in Nam (2004) and Ikegami (1987), but it calls into question the statement put forward by Regier and Zheng (2007) that endpoints (goals) are more finely differentiated semantically than starting points (sources).

Abstract

Gender-(mis)matching pronouns have been studied extensively in experiments. However, a phenomenon common to various languages has thus far been overlooked: the systemic use of non-feminine pronouns when referring to female individuals. The present study is the first to provide experimental insights into the interpretation of such a pronoun: Limburgian zien ‘his/its’ and Dutch zijn ‘his/its’ are grammatically ambiguous between masculine and neuter, but while Limburgian zien can refer to women, the Dutch equivalent zijn cannot. Employing an acceptability judgment task, we presented speakers of Limburgian (N = 51) with recordings of sentences in Limburgian featuring zien, and speakers of Dutch (N = 52) with Dutch translations of these sentences featuring zijn. All sentences featured a potential male or female antecedent embedded in a stereotypically male or female context. We found that ratings were higher for sentences in which the pronoun could refer back to the antecedent. For Limburgians, this extended to sentences mentioning female individuals. Context further modulated sentence appreciation. Possible mechanisms regarding the interpretation of zien as coreferential with a female individual will be discussed.

Abstract

Two eye-tracking experiments tested whether native listeners can adapt
to reductions in casual Dutch speech. Listeners were exposed to segmental
([b] > [m]), syllabic (full-vowel-deletion), or no reductions. In a subsequent
test phase, all three listener groups were tested on how efficiently they could
recognize both types of reduced words. In the first Experiment’s exposure
phase, the (un)reduced target words were predictable. The segmental reductions
were completely consistent (i.e., involved the same input sequences).
Learning about them was found to be pattern-specific and generalized in the
test phase to new reduced /b/-words. The syllabic reductions were not consistent
(i.e., involved variable input sequences). Learning about them was
weak and not pattern-specific. Experiment 2 examined effects of word repetition
and predictability. The (un-)reduced test words appeared in the exposure
phase and were not predictable. There was no evidence of learning for
the segmental reductions, probably because they were not predictable during
exposure. But there was word-specific learning for the vowel-deleted words.
The results suggest that learning about reductions is pattern-specific and
generalizes to new words if the input is consistent and predictable. With
variable input, there is more likely to be adaptation to a general speaking
style and word-specific learning.

Abstract

For the beginning language learner, communicative input is not based on linguistic codes alone. This study investigated two extralinguistic factors which are important for infants’ language development: the type of ongoing shared activity and non-verbal, deictic gestures. The natural interactions of 39 caregivers and their 12-month-old infants were recorded in two semi-natural contexts: a free play situation based on action and manipulation of objects, and a situation based on regard of objects, broadly analogous to an exhibit. Results show that the type of shared activity structures both caregivers’ language usage and caregivers’ and infants’ gesture usage. Further, there is a specific pattern with regard to how caregivers integrate speech with particular deictic gesture types. The findings demonstrate a pervasive influence of shared activities on human communication, even before language has emerged. The type of shared activity and caregivers’ systematic integration of specific forms of deictic gestures with language provide infants with a multimodal scaffold for a usage-based acquisition of language.

Abstract

This paper explores the semantics of the dative in Tashelhiyt, a Berber language from Morocco. After a brief morphosyntactic overview of the dative in this language, I identify a wide range of its semantic roles, including possessor, experiencer, distributive and unintending causer. I arrange these roles in a semantic map and propose semantic links between the roles such as metaphorisation and generalisation. In the light of the Tashelhiyt data, the paper also proposes additions to previous semantic maps of the dative (Haspelmath 1999, 2003) and to Kittilä’s 2005 typology of beneficiary coding.

Abstract

This paper explores the semantics of placement and removal verbs in Ākhoe Hai om based on event descriptions elicited with a set of video stimuli. After a brief sketch of the morphosyntax of placement/removal constructions in Ākhoe Haiom, four situation types are identified semantically that cover both placement and removal events. The language exhibits a clear tendency to make more fine-grained semantic distinctions in placement verbs, as opposed to semantically more general removal verbs.

Abstract

Word count estimation (WCE) from audio recordings has a number of applications, including quantifying the amount of speech that language-learning infants hear in their natural environments, as captured by daylong recordings made with devices worn by infants. To be applicable in a wide range of scenarios and also low-resource domains, WCE tools should be extremely robust against varying signal conditions and require minimal access to labeled training data in the target domain. For this purpose, earlier work has used automatic syllabification of speech, followed by a least-squares-mapping of syllables to word counts. This paper compares a number of previously proposed syllabifiers in the WCE task, including a supervised bi-directional long short-term memory (BLSTM) network that is trained on a language for which high quality syllable annotations are available (a “high resource language”), and reports how the alternative methods compare on different languages and signal conditions. We also explore additive noise and varying-channel data augmentation strategies for BLSTM training, and show how they improve performance in both matching and mismatching languages. Intriguingly, we also find that even though the BLSTM works on languages beyond its training data, the unsupervised algorithms can still outperform it in challenging signal conditions on novel languages.

Abstract

Cognitive research is often focused on experimental condition-driven reactions. Ethological studies frequently
rely on the observation of naturally occurring specific behaviors. In both cases, subjects are filmed during the
study, so that afterwards behaviors can be coded on video. Coding should typically be blind to experimental
conditions, but often requires more information than that present on video. We introduce a method for blindcoding
of behavioral videos that takes care of both issues via three main innovations. First, of particular
significance for playback studies, it allows creation of a “soundtrack” of the study, that is, a track composed of
synthesized sounds representing different aspects of the experimental conditions, or other events, over time.
Second, it facilitates coding behavior using this audio track, together with the possibly muted original video.
This enables coding blindly to conditions as required, but not ignoring other relevant events. Third, our method
makes use of freely available, multi-platform software, including scripts we developed.