Publications

Abstract

In the CLARIN infrastructure various national projects have started initiatives to allow users of the infrastructure to create chains or workflows of web services. The Component Metadata (CMD) core model for web services described in this paper tries to align the metadata descriptions of these various initiatives. This should allow chaining/workflow engines to find matching and invoke services. The paper describes the landscape of web services architectures and the state of the national initiatives. Based on this a CMD core model for CLARIN is proposed, which, within some limits, can be adapted to the specific needs of an initiative by the standard facilities of CMD. The paper closes with the current state and usage of the model and a look into the future.

Abstract

ISO Technical Committee 37, Terminology and other language and content resources, established an ISO 12620:2009 based Data Category Registry (DCR), called ISOcat (see http://www.isocat.org), to foster semantic interoperability of linguistic resources. However, this goal can only be met if the data categories are reused by a wide variety of linguistic resource types. A resource indicates its usage of data categories by linking to them. The small DC Reference XML vocabulary is used to embed links to data categories in XML documents. The link is established by an URI, which servers as the Persistent IDentifier (PID) of a data category. This paper discusses the efforts to mimic the same approach for RDF-based resources. It also introduces the RDF quad store based Relation Registry RELcat, which enables ontological relationships between data categories not supported by ISOcat and thus adds an extra level of linguistic knowledge.

Abstract

The ISOcat Data Category Registry contains basically a flat and easily extensible list of data category specifications. To foster reuse and standardization only very shallow relationships among data categories are stored in the registry. However, to assist crosswalks, possibly based on personal views, between various (application) domains and to overcome possible proliferation of data categories more types of ontological relationships need to be specified. RELcat is a first prototype of a Relation Registry, which allows storing arbitrary relationships. These relationships can reflect the personal view of one linguist or a larger community. The basis of the registry is a relation type taxonomy that can easily be extended. This allows on one hand to load existing sets of relations specified in, for example, an OWL (2) ontology or SKOS taxonomy. And on the other hand allows algorithms that query the registry to traverse the stored semantic network to remain ignorant of the original source vocabulary. This paper describes first experiences with RELcat and explains some initial design decisions.

Abstract

Automatic Language Identification of written texts is a well-established area of research in Computational Linguistics. State-of-the-art algorithms often rely on n-gram character models to identify the correct language of texts, with good results seen for European languages. In this paper we propose the use of a character n-gram model and a word n-gram language model for the automatic classification of two written varieties of Portuguese: European and Brazilian. Results reached 0.998 for accuracy using character 4-grams.

Abstract

Arbil is an application designed to create and manage metadata for research data and to arrange this data into a structure appropriate for archiving. The metadata is displayed in tables, which allows an overview of the metadata and the ability to populate and update many metadata sections in bulk. Both IMDI and Clarin metadata formats are supported and Arbil has been designed as a local application so that it can also be used offline, for instance in remote field sites. The metadata can be entered in any order or at any stage that the user is able; once the metadata and its data are ready for archiving and an Internet connection is available it can be exported from Arbil and in the case of IMDI it can then be transferred to the main archive via LAMUS (archive management and upload system).

Abstract

We investigated how the strength of a foreign accent and varying types of experience with foreign-accented speech influence the recognition of accented words. In Experiment 1, native Dutch listeners with limited or extensive prior experience with German-accented Dutch completed a cross-modal priming experiment with strongly, medium, and weakly accented words. Participants with limited experience were primed by the medium and weakly accented words, but not by the strongly accented words. Participants with extensive experience were primed by all accent types. In Experiments 2 and 3, Dutch listeners with limited experience listened to a short story before doing the cross-modal priming task. In Experiment 2, the story was spoken by the priming task speaker and either contained strongly accented words or did not. Strongly accented exposure led to immediate priming by novel strongly accented words, while exposure to the speaker without strongly accented tokens led to priming only in the experiment’s second half. In Experiment 3, listeners listened to the story with strongly accented words spoken by a different German-accented speaker. Listeners were primed by the strongly accented words, but again only in the experiment’s second half. Together, these results show that adaptation to foreign-accented speech is rapid but depends on accent strength and on listener familiarity with those strongly accented words.

Abstract

Introduction Speech research saw a dramatic change in paradigm in the 90-ies. While earlier the discussion was dominated by a phoneticians’ approach who knew about phenomena in the speech signal, the situation completely changed after stochastic machinery such as Hidden Markov Models [1] and Artificial Neural Networks [2] had been introduced. Speech processing was now dominated by a purely mathematic approach that basically ignored all existing knowledge about the speech production process and the perception mechanisms. The key was now to construct a large enough training set that would allow identifying the many free parameters of such stochastic engines. In case that the training set is representative and the annotations of the training sets are widely ‘correct’ we could assume to get a satisfyingly functioning recognizer. While the success of knowledge-based systems such as Hearsay II [3] was limited, the statistically based approach led to great improvements in recognition rates and to industrial applications.

Abstract

5.1 Einführung in den Forschungsbereich Die Psycholinguistik ist der Bereich der Linguistik, der sich mit dem Zusammenhang zwischen menschlicher Sprache und dem Denken und anderen mentalen Prozessen beschäftigt, d.h. sie stellt sich einer Reihe von essentiellen Fragen wie etwa (1) Wie schafft es unser Gehirn, im Wesentlichen akustische und visuelle kommunikative Informationen zu verstehen und in mentale Repräsentationen umzusetzen? (2) Wie kann unser Gehirn einen komplexen Sachverhalt, den wir anderen übermitteln wollen, in eine von anderen verarbeitbare Sequenz von verbalen und nonverbalen Aktionen umsetzen? (3) Wie gelingt es uns, in den verschiedenen Phasen des Lebens Sprachen zu erlernen? (4) Sind die kognitiven Prozesse der Sprachverarbeitung universell, obwohl die Sprachsysteme derart unterschiedlich sind, dass sich in den Strukturen kaum Universalien finden lassen?

Abstract

According to a widely-held view among various scholars, olfaction is inferior to other human senses. It is also believed by many that languages do not have words for describing smells. Data collected among the Maniq, a small population of nomadic foragers in southern Thailand, challenge the above claims and point to a great linguistic and cultural elaboration of odor. This article presents evidence of the importance of olfaction in indigenous rituals and beliefs, as well as in the lexicon. The results demonstrate the richness and complexity of the domain of smell in Maniq society and thereby challenge the universal paucity of olfactory terms and insignificance of olfaction for humans.

Abstract

Brain processing depends on the interactions between neuronal groups. Those interactions are governed by the pattern of anatomical connections and by yet unknown mechanisms that modulate the effective strength of a given connection. We found that the mutual influence among neuronal groups depends on the phase relation between rhythmic activities within the groups. Phase relations supporting interactions between the groups preceded those interactions by a few milliseconds, consistent with a mechanistic role. These effects were specific in time, frequency, and space, and we therefore propose that the pattern of synchronization flexibly determines the pattern of neuronal interactions.

Abstract

The ISOcat Data Category Registry provides a community computing environment for creating, storing, retrieving, harmonizing and standardizing data category specifications (DCs), used to register linguistic terms used in various fields. This chapter recounts the history of DC documentation in TC 37, beginning from paper-based lists created for lexicographers and terminologists and progressing to the development of a web-based resource for a much broader range of users. While describing the considerable strides that have been made to collect a very large comprehensive collection of DCs, it also outlines difficulties that have arisen in developing a fully operative web-based computing environment for achieving consensus on data category names, definitions, and selections and describes efforts to overcome some of the present shortcomings and to establish positive working procedures designed to engage a wide range of people involved in the creation of language resources.

Abstract

Im ISOcat-Datenkategorie-Register (Data Category Registry, www.isocat.org) des Technischen Komitees ISO/TC 37 (Terminology and other language and content resources) werden Feldnamen und Werte für Sprachressourcen beschrieben. Empfohlene Feldnamen und zuverlässige Definitionen sollen dazu beitragen, dass Sprachdaten unabhängig von Anwendungen, Plattformen und Communities of Practice (CoP) wiederverwendet werden können. Datenkategorie-Gruppen (Data Category Selections) können eingesehen, ausgedruckt, exportiert und nach kostenloser Registrierung auch neu erstellt werden.

Abstract

We carried out the first study on the relationship between individual language aptitude and structural connectivity of language pathways in the adult brain. We measured four components of language aptitude (vocabulary learning, VocL; sound recognition, SndRec; sound-symbol correspondence, SndSym; and grammatical inferencing, GrInf) using the LLAMA language aptitude test (Meara, 2005). Spatial working memory (SWM), verbal working memory (VWM) and IQ were also measured as control factors. Diffusion Tensor Imaging (DTI) was employed to investigate the structural connectivity of language pathways in the perisylvian language network. Principal Component Analysis (PCA) on behavioural measures suggests that a general ability might be important to the first stages of L2 acquisition. It also suggested that VocL, SndSy and SWM are more closely related to general IQ than SndRec and VocL, and distinguished the tasks specifically designed to tap into L2 acquisition (VocL, SndRec,SndSym and GrInf) from more generic measures (IQ, SWM and VWM). Regression analysis suggested significant correlations between most of these behavioural measures and the structural connectivity of certain language pathways, i.e., VocL and BA47-Parietal pathway, SndSym and inter-hemispheric BA45 pathway, GrInf and BA45-Temporal pathway and BA6-Temporal pathway, IQ and BA44-Parietal pathway, BA47-Parietal pathway, BA47-Temporal pathway and inter-hemispheric BA45 pathway, SWM and inter-hemispheric BA6 pathway and BA47-Parietal pathway, and VWM and BA47-Temporal pathway. These results are discussed in relation to relevant findings in the literature.

Abstract

In recent decades, neuroimaging studies on the neural infrastructure of language are usually (or mostly) conducted with certain on-line language processing tasks. These functional neuroimaging studies helped to localize the language areas in the brain and to investigate the brain activity during explicit language processing. However, little is known about what is going on with the language areas when the brain is ‘at rest’, i.e., when there is no explicit language processing running. Taking advantage of the fcMRI and DTI techniques, this thesis is able to investigate the language function ‘off-line’ at the neuronal network level and the connectivity among language areas in the brain. Based on patient studies, the traditional, classical model on the perisylvian language network specifies a “Broca’ area – Arcuate Fasciculus – Werinicke’s area” loop (Ojemann 1991). With the help of modern neuroimaging techniques, researchers have been able to track language pathways that involve more brain structures than are in the classical model, and relate them to certain language functions. In such a background, a large part of this thesis made a contribution to the study of the topology of the language networks. It revealed that the language networks form a topographical functional connectivity pattern in the left hemisphere for the right-handers. This thesis also revealed the importance of structural hubs, such as Broca’s and Wernicke’s areas, which have more connectivity to other brain areas and play a central role in the language networks. Furthermore, this thesis revealed both functionally and structurally lateralized language networks in the brain. The consistency between what is found in this thesis and what has been known from previous functional studies seems to suggest, that the human brain is optimized and ‘ready’ for the language function even when there is currently no explicit language-processing running.

Abstract

Four experiments investigated the role of the syllable in Chinese spoken word production. Chen, Chen and Ferrand (2003) reported a syllable priming effect when primes and targets shared the first syllable using a masked priming paradigm in Chinese. Our Experiment 1 was a direct replication of Chen et al.'s (2003) Experiment 3 employing CV (e. g., /ba2.ying2/, strike camp) and CVG (e. g., /bai2.shou3/, white haired) syllable types. Experiment 2 tested the syllable priming effect using different syllable types: e. g., CV (/qi4.qiu2/, balloon) and CVN (/qing1.ting2/, dragonfly). Experiment 3 investigated this issue further using line drawings of common objects as targets that were preceded either by a CV (e. g., /qi3/, attempt), or a CVN (e. g., /qing2/, affection) prime. Experiment 4 further examined the priming effect by a comparison between CV or CVN priming and an unrelated priming condition using CV-NX (e. g., /mi2.ni3/, mini) and CVN-CX (e. g., /min2.ju1/, dwellings) as target words. These four experiments consistently found that CV targets were named faster when preceded by CV primes than when they were preceded by CVG, CVN or unrelated primes, whereas CVG or CVN targets showed the reverse pattern. These results indicate that the priming effect critically depends on the match between the structure of the prime and that of the first syllable of the target. The effect obtained in this study was consistent across different stimuli and different tasks (word and picture naming), and provides more conclusive and consistent data regarding the role of the syllable in Chinese speech production.

Abstract

Automatic Language Identification of written texts is a well-established area of research in Computational Linguistics. State-of-the-art algorithms often rely on n-gram character models to identify the correct language of texts, with good results seen for European languages. In this paper we propose the use of a character n-gram model and a word n-gram language model for the automatic classification of two written varieties of Portuguese: European and Brazilian. Results reached 0.998 for accuracy using character 4-grams.

Abstract

This study presents a new language identification model for pluricentric languages that uses n-gram language models at the character and word level. The model is evaluated in two steps. The first step consists of the identification of two varieties of Spanish (Argentina and Spain) and two varieties of French (Quebec and France) evaluated independently in binary classification schemes. The second step integrates these language models in a six-class classification with two Portuguese varieties.

Abstract

This article presents data on cardinal numerals in three sign languages from small-scale communities with hereditary deafness. The unusual features found in these data considerably extend the known range of typological variety across sign languages. Some features, such as non-decimal numeral bases, are unattested in sign languages, but familiar from spoken languages, while others, such as subtractive sub-systems, are rare in sign and speech. We conclude that for a complete typological appraisal of a domain, an approach to cross-modal typology, which includes a typologically diverse range of sign languages in addition to spoken languages, is both instructive and feasible.

Abstract

The book is a unique collection of research on sign languages that have emerged in rural communities with a high incidence of, often hereditary, deafness. These sign languages represent the latest addition to the comparative investigation of languages in the gestural modality, and the book is the first compilation of a substantial number of different "village sign languages".Written by leading experts in the field, the volume uniquely combines anthropological and linguistic insights, looking at both the social dynamics and the linguistic structures in these village communities. The book includes primary data from eleven different signing communities across the world, including results from Jamaica, India, Turkey, Thailand, and Bali. All known village sign languages are endangered, usually because of pressure from larger urban sign languages, and some have died out already. Ironically, it is often the success of the larger sign language communities in urban centres, their recognition and subsequent spread, which leads to the endangerment of these small minority sign languages. The book addresses this specific type of language endangerment, documentation strategies, and other ethical issues pertaining to these sign languages on the basis of first-hand experiences by Deaf fieldworkers

Abstract

Semantic unification, the process by which small blocks of semantic information are combined into a coherent utterance, has been studied with various types of tasks. However, whether the brain activations reported in these studies are attributed to semantic unification per se or to other task-induced concomitant processes still remains unclear. The neural basis for semantic unification in sentence comprehension was examined using event-related potentials (ERP) and functional Magnetic Resonance Imaging (fMRI). The semantic unification load was manipulated by varying the goodness of fit between a critical word and its preceding context (in high cloze, low cloze and violation sentences). The sentences were presented in a serial visual presentation mode. The participants were asked to perform one of three tasks: semantic congruency judgment (SEM), silent reading for comprehension (READ), or font size judgment (FONT), in separate sessions. The ERP results showed a similar N400 amplitude modulation by the semantic unification load across all of the three tasks. The brain activations associated with the semantic unification load were found in the anterior left inferior frontal gyrus (aLIFG) in the FONT task and in a widespread set of regions in the other two tasks. These results suggest that the aLIFG activation reflects a semantic unification, which is different from other brain activations that may reflect task-specific strategic processing.

Abstract

Genome-wide association studies using thousands to hundreds of thousands of single nucleotide polymorphism (SNP) markers and region-wide association studies using a dense panel of SNPs are already in use to identify disease susceptibility genes and to predict disease risk in individuals. Because these tasks become increasingly important, three different data sets were provided for the Genetic Analysis Workshop 15, thus allowing examination of various novel and existing data mining methods for both classification and identification of disease susceptibility genes, gene by gene or gene by environment interaction. The approach most often applied in this presentation group was random forests because of its simplicity, elegance, and robustness. It was used for prediction and for screening for interesting SNPs in a first step. The logistic tree with unbiased selection approach appeared to be an interesting alternative to efficiently select interesting SNPs. Machine learning, specifically ensemble methods, might be useful as pre-screening tools for large-scale association studies because they can be less prone to overfitting, can be less computer processor time intensive, can easily include pair-wise and higher-order interactions compared with standard statistical approaches and can also have a high capability for classification. However, improved implementations that are able to deal with hundreds of thousands of SNPs at a time are required.

Abstract

Psycholinguistic research has typically portrayed speech production as a relatively automatic process. This is because when errors are made, they occur as seldom as one in every thousand words we utter. However, it has long been recognised that we need some form of control over what we are currently saying and what we plan to say. This capacity to both monitor our inner speech and self-correct our speech output has often been assumed to be a property of the language comprehension system. More recently, it has been demonstrated that speech production benefits from interfacing with more general cognitive processes such as selective attention, short-term memory (STM) and online response monitoring to resolve potential conflict and successfully produce the output of a verbal plan. The conditions and levels of representation according to which these more general planning, monitoring and control processes are engaged during speech production remain poorly understood. Moreover, there remains a paucity of information about their neural substrates, despite some of the first evidence of more general monitoring having come from electrophysiological studies of error related negativities (ERNs). While aphasic speech errors continue to be a rich source of information, there has been comparatively little research focus on instances of speech repair. The purpose of this Frontiers Research Topic is to provide a forum for researchers to contribute investigations employing behavioural, neuropsychological, electrophysiological, neuroimaging and virtual lesioning techniques. In addition, while the focus of the research topic is on novel findings, we welcome submission of computational simulations, review articles and methods papers.

Abstract

How does language comprehension interact with motor activity? We investigated the conditions under which comprehending an action sentence affects people's balance. We performed two experiments to assess whether sentences describing forward or backward movement modulate the lateral movements made by subjects who made sensibility judgments about the sentences. In one experiment subjects were standing on a balance board and in the other they were seated on a balance board that was mounted on a chair. This allowed us to investigate whether the action compatibility effect (ACE) is robust and persists in the face of salient incompatibilities between sentence content and subject movement. Growth-curve analysis of the movement trajectories produced by the subjects in response to the sentences suggests that the ACE is indeed robust. Sentence content influenced movement trajectory despite salient inconsistencies between implied and actual movement. These results are interpreted in the context of the current discussion of embodied, or grounded, language comprehension and meaning representation.

Abstract

Classifiers (currently also called 'depicting handshapes'), are observed in almost all signed languages studied to date and form a well-researched topic in sign language linguistics. Yet, these elements are still subject to much debate with respect to a variety of matters. Several different categories of classifiers have been posited on the basis of their semantics and the linguistic context in which they occur. The function(s) of classifiers are not fully clear yet. Similarly, there are differing opinions regarding their structure and the structure of the signs in which they appear. Partly as a result of comparison to classifiers in spoken languages, the term 'classifier' itself is under debate. In contrast to these disagreements, most studies on the acquisition of classifier constructions seem to consent that these are difficult to master for Deaf children. This article presents and discusses all these issues from the viewpoint that classifiers are linguistic elements.

Abstract

This paper explores the expression of multiple entities in Turkish Sign Language (Türk İşaret Dili; TİD), a less well-studied sign language. It aims to provide a comprehensive description of the ways and frequencies in which entity plurality in this language is expressed, both within and outside the noun phrase. We used a corpus that includes both elicited and spontaneous data from native signers. The results reveal that most of the expressions of multiple entities in TİD are iconic, spatial strategies (i.e. localization and spatial plural predicate inflection) none of which, we argue, should be considered as genuine plural marking devices with the main aim of expressing plurality. Instead, the observed devices for localization and predicate inflection allow for a plural interpretation when multiple locations in space are used. Our data do not provide evidence that TİD employs (productive) morphological plural marking (i.e. reduplication) on nouns, in contrast to some other sign languages and many spoken languages. We relate our findings to expression of multiple entities in other signed languages and in spoken languages and discuss these findings in terms of modality effects on expression of multiple entities in human language.

Abstract

This paper reports on an exploration of the ways in which multiple entities are expressed in Turkish Sign Language (TİD). The (descriptive and quantitative) analyses provided are based on a corpus of both spontaneous data and specifically elicited data, in order to provide as comprehensive an account as possible. We have found several devices in TİD for expression of multiple entities, in particular localization, spatial plural predicate inflection, and a specific form used to express multiple entities that are side by side in the same configuration (not reported for any other sign language to date), as well as numerals and quantifiers. In contrast to some other signed languages, TİD does not appear to have a productive system of plural reduplication. We argue that none of the devices encountered in the TİD data is a genuine plural marking device and that the plural interpretation of multiple entity localizations and plural predicate inflections is a by-product of the use of space to indicate the existence or the involvement in an event of multiple entities.