Publications

Displaying 601 - 615 of 615
  • 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.
  • Witteman, M. J., Bardhan, N. P., Weber, A., & McQueen, J. M. (2011). Adapting to foreign-accented speech: The role of delay in testing. Journal of the Acoustical Society of America. Program abstracts of the 162nd Meeting of the Acoustical Society of America, 130(4), 2443.

    Abstract

    Understanding speech usually seems easy, but it can become noticeably harder when the speaker has a foreign accent. This is because foreign accents add considerable variation to speech. Research on foreign-accented speech shows that participants are able to adapt quickly to this type of variation. Less is known, however, about longer-term maintenance of adaptation. The current study focused on long-term adaptation by exposing native listeners to foreign-accented speech on Day 1, and testing them on comprehension of the accent one day later. Comprehension was thus not tested immediately, but only after a 24 hour period. On Day 1, native Dutch listeners listened to the speech of a Hebrew learner of Dutch while performing a phoneme monitoring task that did not depend on the talker’s accent. In particular, shortening of the long vowel /i/ into /ɪ/ (e.g., lief [li:f], ‘sweet’, pronounced as [lɪf]) was examined. These mispronunciations did not create lexical ambiguities in Dutch. On Day 2, listeners participated in a cross-modal priming task to test their comprehension of the accent. The results will be contrasted with results from an experiment without delayed testing and related to accounts of how listeners maintain adaptation to foreign-accented speech.
  • Witteman, M. J., Weber, A., & McQueen, J. M. (2011). On the relationship between perceived accentedness, acoustic similarity, and processing difficulty in foreign-accented speech. In Proceedings of the 12th Annual Conference of the International Speech Communication Association (Interspeech 2011), Florence, Italy (pp. 2229-2232).

    Abstract

    Foreign-accented speech is often perceived as more difficult to understand than native speech. What causes this potential difficulty, however, remains unknown. In the present study, we compared acoustic similarity and accent ratings of American-accented Dutch with a cross-modal priming task designed to measure online speech processing. We focused on two Dutch diphthongs: ui and ij. Though both diphthongs deviated from standard Dutch to varying degrees and perceptually varied in accent strength, native Dutch listeners recognized words containing the diphthongs easily. Thus, not all foreign-accented speech hinders comprehension, and acoustic similarity and perceived accentedness are not always predictive of processing difficulties.
  • Wittenburg, P. (2004). The IMDI metadata concept. In S. F. Ferreira (Ed.), Workingmaterial on Building the LR&E Roadmap: Joint COCOSDA and ICCWLRE Meeting, (LREC2004). Paris: ELRA - European Language Resources Association.
  • Wittenburg, P., Brugman, H., Broeder, D., & Russel, A. (2004). XML-based language archiving. In Workshop Proceedings on XML-based Richly Annotaded Corpora (LREC2004) (pp. 63-69). Paris: ELRA - European Language Resources Association.
  • 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., Gulrajani, G., Broeder, D., & Uneson, M. (2004). Cross-disciplinary integration of metadata descriptions. In M. Lino, M. Xavier, F. Ferreira, R. Costa, & R. Silva (Eds.), Proceedings of the 4th International Conference on Language Resources and Evaluation (LREC2004) (pp. 113-116). Paris: ELRA - European Language Resources Association.
  • Wittenburg, P., Johnson, H., Buchhorn, M., Brugman, H., & Broeder, D. (2004). Architecture for distributed language resource management and archiving. In M. Lino, M. Xavier, F. Ferreira, R. Costa, & R. Silva (Eds.), Proceedings of the 4th International Conference on Language Resources and Evaluation (LREC2004) (pp. 361-364). Paris: ELRA - 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.
  • Zeshan, U., & Panda, S. (2011). Reciprocals constructions in Indo-Pakistani sign language. In N. Evans, & A. Gaby (Eds.), Reciprocals and semantic typology (pp. 91-113). Amsterdam: Benjamins.

    Abstract

    Indo-Pakistani Sign Language (IPSL) is the sign language used by deaf communities in a large region across India and Pakistan. This visual-gestural language has a dedicated construction for specifically expressing reciprocal relationships, which can be applied to agreement verbs and to auxiliaries. The reciprocal construction relies on a change in the movement pattern of the signs it applies to. In addition, IPSL has a number of other strategies which can have a reciprocal interpretation, and the IPSL lexicon includes a good number of inherently reciprocal signs. All reciprocal expressions can be modified in complex ways that rely on the grammatical use of the sign space. Considering grammaticalisation and lexicalisation processes linking some of these constructions is also important for a better understanding of reciprocity in IPSL.
  • Zhang, Y., & Yu, C. (2017). How misleading cues influence referential uncertainty in statistical cross-situational learning. In M. LaMendola, & J. Scott (Eds.), Proceedings of the 41st Annual Boston University Conference on Language Development (BUCLD 41) (pp. 820-833). Boston, MA: Cascadilla Press.
  • 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.

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