Publications

Displaying 301 - 319 of 319
  • Weber, A., & Broersma, M. (2012). Spoken word recognition in second language acquisition. In C. A. Chapelle (Ed.), The encyclopedia of applied linguistics. Bognor Regis: Wiley-Blackwell. doi:10.1002/9781405198431.wbeal1104.

    Abstract

    In order to decode the message of a speaker, listeners have to recognize individual words in the speaker's utterance.
  • Weissenborn, J. (1981). L'acquisition des prepositions spatiales: problemes cognitifs et linguistiques. In C. Schwarze (Ed.), Analyse des prépositions: IIIme colloque franco-allemand de linguistique théorique du 2 au 4 février 1981 à Constance (pp. 251-285). Tübingen: Niemeyer.
  • Windhouwer, M., Petro, J., Newskaya, I., Drude, S., Aristar-Dry, H., & Gippert, J. (2013). Creating a serialization of LMF: The experience of the RELISH project. In G. Francopoulo (Ed.), LMF - Lexical Markup Framework (pp. 215-226). London: Wiley.
  • Windhouwer, M., Broeder, D., & Van Uytvanck, D. (2012). A CMD core model for CLARIN web services. In Proceedings of LREC 2012: 8th International Conference on Language Resources and Evaluation (pp. 41-48).

    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.
  • Windhouwer, M., & Wright, S. E. (2012). Linking to linguistic data categories in ISOcat. In C. Chiarcos, S. Nordhoff, & S. Hellmann (Eds.), Linked data in linguistics: Representing and connecting language data and language metadata (pp. 99-107). Berlin: Springer.

    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.
  • Windhouwer, M., & Wright, S. E. (2013). LMF and the Data Category Registry: Principles and application. In G. Francopoulo (Ed.), LMF: Lexical Markup Framework (pp. 41-50). London: Wiley.
  • Windhouwer, M. (2012). RELcat: a Relation Registry for ISOcat data categories. In N. Calzolari (Ed.), Proceedings of LREC 2012: 8th International Conference on Language Resources and Evaluation (pp. 3661-3664). European Language Resources Association (ELRA).

    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.
  • Windhouwer, M. (2012). Towards standardized descriptions of linguistic features: ISOcat and procedures for using common data categories. In J. Jancsary (Ed.), Proceedings of the Conference on Natural Language Processing 2012, (SFLR 2012 workshop), September 19-21, 2012, Vienna (pp. 494). Vienna: Österreichischen Gesellschaft für Artificial Intelligende (ÖGAI).

    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.
  • Withers, P. (2012). Metadata management with Arbil. In V. Arranz, D. Broeder, B. Gaiffe, M. Gavrilidou, & M. Monachini (Eds.), Proceedings of LREC 2012: 8th International Conference on Language Resources and Evaluation (pp. 72-75). European Language Resources Association (ELRA).

    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).
  • Wittek, A. (1998). Learning verb meaning via adverbial modification: Change-of-state verbs in German and the adverb "wieder" again. In A. Greenhill, M. Hughes, H. Littlefield, & H. Walsh (Eds.), Proceedings of the 22nd Annual Boston University Conference on Language Development (pp. 779-790). Somerville, MA: Cascadilla Press.
  • Wittenburg, P., Lenkiewicz, P., Auer, E., Gebre, B. G., Lenkiewicz, A., & Drude, S. (2012). AV Processing in eHumanities - a paradigm shift. In J. C. Meister (Ed.), Digital Humanities 2012 Conference Abstracts. University of Hamburg, Germany; July 16–22, 2012 (pp. 538-541).

    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.
  • Wittenburg, P., & Ringersma, J. (2013). Metadata description for lexicons. In R. H. Gouws, U. Heid, W. Schweickard, & H. E. Wiegand (Eds.), Dictionaries: An international encyclopedia of lexicography: Supplementary volume: Recent developments with focus on electronic and computational lexicography (pp. 1329-1335). Berlin: Mouton de Gruyter.
  • Wittenburg, P., Drude, S., & Broeder, D. (2012). Psycholinguistik. In H. Neuroth, S. Strathmann, A. Oßwald, R. Scheffel, J. Klump, & J. Ludwig (Eds.), Langzeitarchivierung von Forschungsdaten. Eine Bestandsaufnahme (pp. 83-108). Boizenburg: Verlag Werner Hülsbusch.

    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?
  • Wnuk, E., & Majid, A. (2012). Olfaction in a hunter-gatherer society: Insights from language and culture. In N. Miyake, D. Peebles, & R. P. Cooper (Eds.), Proceedings of the 34th Annual Meeting of the Cognitive Science Society (CogSci 2012) (pp. 1155-1160). Austin, TX: Cognitive Science Society.

    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.
  • Wright, S. E., Windhouwer, M., Schuurman, I., & Kemps-Snijders, M. (2013). Community efforts around the ISOcat Data Category Registry. In I. Gurevych, & J. Kim (Eds.), The People's Web meets NLP: Collaboratively constructed language resources (pp. 349-374). New York: Springer.

    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.
  • Zampieri, M., & Gebre, B. G. (2012). Automatic identification of language varieties: The case of Portuguese. In J. Jancsary (Ed.), Proceedings of the Conference on Natural Language Processing 2012, September 19-21, 2012, Vienna (pp. 233-237). Vienna: Österreichischen Gesellschaft für Artificial Intelligende (ÖGAI).

    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.
  • Zampieri, M., Gebre, B. G., & Diwersy, S. (2012). Classifying pluricentric languages: Extending the monolingual model. In Proceedings of SLTC 2012. The Fourth Swedish Language Technology Conference. Lund, October 24-26, 2012 (pp. 79-80). Lund University.

    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.
  • Zwitserlood, I. (2012). Classifiers. In R. Pfau, M. Steinbach, & B. Woll (Eds.), Sign Language: an International Handbook (pp. 158-186). Berlin: Mouton de Gruyter.

    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.
  • Zwitserlood, I., Perniss, P. M., & Ozyurek, A. (2013). Expression of multiple entities in Turkish Sign Language (TİD). In E. Arik (Ed.), Current Directions in Turkish Sign Language Research (pp. 272-302). Newcastle upon Tyne: Cambridge Scholars Publishing.

    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.

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