Publications

Displaying 301 - 310 of 310
  • Wanrooij, K., De Vos, J., & Boersma, P. (2015). Distributional vowel training may not be effective for Dutch adults. In Scottish consortium for ICPhS 2015, M. Wolters, J. Livingstone, B. Beattie, R. Smith, M. MacMahon, J. Stuart-Smith, & J. Scobbie (Eds.), Proceedings of the 18th International Congress of Phonetic Sciences (ICPhS 2015). Glasgow: University of Glasgow.

    Abstract

    Distributional vowel training for adults has been reported as “effective” for Spanish and Bulgarian learners of Dutch vowels, in studies using a behavioural task. A recent study did not yield a similar clear learning effect for Dutch learners of the English vowel contrast /æ/~/ε/, as measured with event-related potentials (ERPs). The present study aimed to examine the possibility that the latter result was related to the method. As in the ERP study, we tested whether distributional training improved Dutch adult learners’ perception of English /æ/~/ε/. However, we measured behaviour instead of ERPs, in a design identical to that used in the previous studies with Spanish learners. The results do not support an effect of distributional training and thus “replicate” the ERP study. We conclude that it remains unclear whether distributional vowel training is effective for Dutch adults.
  • Willems, R. M. (Ed.). (2015). Cognitive neuroscience of natural language use. Cambridge: Cambridge University Press.
  • Willems, R. M. (2015). Cognitive neuroscience of natural language use: Introduction. In Cognitive neuroscience of natural language use (pp. 1-7). Cambridge: Cambridge University Press.
  • 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., & 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.
  • 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.
  • 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.
  • 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.
  • Zhang, Y., Yurovsky, D., & Yu, C. (2015). Statistical word learning is a continuous process: Evidence from the human simulation paradigm. In D. Noelle, R. Dale, A. Warlaumont, J. Yoshimi, T. Matlock, C. D. Jennings, & P. P. Maglio (Eds.), Proceedings of the 37th Annual Meeting of the Cognitive Science Society (CogSci 2015) (pp. 2422-2427). Austin: Cognitive Science Society.

    Abstract

    In the word-learning domain, both adults and young children are able to find the correct referent of a word from highly ambiguous contexts that involve many words and objects by computing distributional statistics across the co-occurrences of words and referents at multiple naming moments (Yu & Smith, 2007; Smith & Yu, 2008). However, there is still debate regarding how learners accumulate distributional information to learn object labels in natural learning environments, and what underlying learning mechanism learners are most likely to adopt. Using the Human Simulation Paradigm (Gillette, Gleitman, Gleitman & Lederer, 1999), we found that participants’ learning performance gradually improved and that their ability to remember and carry over partial knowledge from past learning instances facilitated subsequent learning. These results support the statistical learning model that word learning is a continuous process.
  • 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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