Publications

Displaying 401 - 419 of 419
  • 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., Kita, S., & Brugman, H. (2002). Crosslinguistic studies of multimodal communication.
  • Wittenburg, P., Peters, W., & Drude, S. (2002). Analysis of lexical structures from field linguistics and language engineering. In M. R. González, & C. P. S. Araujo (Eds.), Third international conference on language resources and evaluation (pp. 682-686). Paris: European Language Resources Association.

    Abstract

    Lexica play an important role in every linguistic discipline. We are confronted with many types of lexica. Depending on the type of lexicon and the language we are currently faced with a large variety of structures from very simple tables to complex graphs, as was indicated by a recent overview of structures found in dictionaries from field linguistics and language engineering. It is important to assess these differences and aim at the integration of lexical resources in order to improve lexicon creation, exchange and reuse. This paper describes the first step towards the integration of existing structures and standards into a flexible abstract model.
  • Wittenburg, P., & Broeder, D. (2002). Metadata overview and the semantic web. In P. Austin, H. Dry, & P. Wittenburg (Eds.), Proceedings of the international LREC workshop on resources and tools in field linguistics. Paris: European Language Resources Association.

    Abstract

    The increasing quantity and complexity of language resources leads to new management problems for those that collect and those that need to preserve them. At the same time the desire to make these resources available on the Internet demands an efficient way characterizing their properties to allow discovery and re-use. The use of metadata is seen as a solution for both these problems. However, the question is what specific requirements there are for the specific domain and if these are met by existing frameworks. Any possible solution should be evaluated with respect to its merit for solving the domain specific problems but also with respect to its future embedding in “global” metadata frameworks as part of the Semantic Web activities.
  • Wittenburg, P., Peters, W., & Broeder, D. (2002). Metadata proposals for corpora and lexica. In M. Rodriguez González, & C. Paz Suárez Araujo (Eds.), Third international conference on language resources and evaluation (pp. 1321-1326). Paris: European Language Resources Association.
  • Wittenburg, P., Broeder, D., Offenga, F., & Willems, D. (2002). Metadata set and tools for multimedia/multimodal language resources. In M. Maybury (Ed.), Proceedings of the 3rd International Conference on Language Resources and Evaluation (LREC 2002). Workshop on Multimodel Resources and Multimodel Systems Evaluation. (pp. 9-13). Paris: European Language Resources Association.
  • Wittenburg, P., Mosel, U., & Dwyer, A. (2002). Methods of language documentation in the DOBES program. In P. Austin, H. Dry, & P. Wittenburg (Eds.), Proceedings of the international LREC workshop on resources and tools in field linguistics (pp. 36-42). Paris: European Language Resources Association.
  • 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.
  • 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. (2002). Klassifikatoren in der Niederländischen Gebärdensprache (NGT). In H. Leuniger, & K. Wempe (Eds.), Gebärdensprachlinguistik 2000. Theorie und Anwendung. Vorträge vom Symposium "Gebärdensprachforschung im deutschsprachigem Raum", Frankfurt a.M., 11.-13. Juni 1999 (pp. 113-126). Hamburg: Signum Verlag.
  • Zwitserlood, I. (2002). The complex structure of ‘simple’ signs in NGT. In J. Van Koppen, E. Thrift, E. Van der Torre, & M. Zimmermann (Eds.), Proceedings of ConSole IX (pp. 232-246).

    Abstract

    In this paper, I argue that components in a set of simple signs in Nederlandse Gebarentaal (also called Sign Language of the Netherlands; henceforth: NGT), i.e. hand configuration (including orientation), movement and place of articulation, can also have morphological status. Evidence for this is provided by: firstly, the fact that handshape, orientation, movement and place of articulation show regular meaningful patterns in signs, which patterns also occur in newly formed signs, and secondly, the gradual change of formerly noninflecting predicates into inflectional predicates. The morphological complexity of signs can best be accounted for in autosegmental morphological templates.
  • Zwitserlood, I. (2003). Word formation below and above little x: Evidence from Sign Language of the Netherlands. In Proceedings of SCL 19. Nordlyd Tromsø University Working Papers on Language and Linguistics (pp. 488-502).

    Abstract

    Although in many respects sign languages have a similar structure to that of spoken languages, the different modalities in which both types of languages are expressed cause differences in structure as well. One of the most striking differences between spoken and sign languages is the influence of the interface between grammar and PF on the surface form of utterances. Spoken language words and phrases are in general characterized by sequential strings of sounds, morphemes and words, while in sign languages we find that many phonemes, morphemes, and even words are expressed simultaneously. A linguistic model should be able to account for the structures that occur in both spoken and sign languages. In this paper, I will discuss the morphological/ morphosyntactic structure of signs in Nederlandse Gebarentaal (Sign Language of the Netherlands, henceforth NGT), with special focus on the components ‘place of articulation’ and ‘handshape’. I will focus on their multiple functions in the grammar of NGT and argue that the framework of Distributed Morphology (DM), which accounts for word formation in spoken languages, is also suited to account for the formation of structures in sign languages. First I will introduce the phonological and morphological structure of NGT signs. Then, I will briefly outline the major characteristics of the DM framework. Finally, I will account for signs that have the same surface form but have a different morphological structure by means of that framework.

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