Publications

Displaying 301 - 305 of 305
  • 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.
  • Zinn, C., Cablitz, G., Ringersma, J., Kemps-Snijders, M., & Wittenburg, P. (2008). Constructing knowledge spaces from linguistic resources. In Proceedings of the CIL 18 Workshop on Linguistic Studies of Ontology: From lexical semantics to formal ontologies and back.
  • Zinn, C. (2008). Conceptual spaces in ViCoS. In S. Bechhofer, M. Hauswirth, J. Hoffmann, & M. Koubarakis (Eds.), The semantic web: Research and applications (pp. 890-894). Berlin: Springer.

    Abstract

    We describe ViCoS, a tool for constructing and visualising conceptual spaces in the area of language documentation. ViCoS allows users to enrich existing lexical information about the words of a language with conceptual knowledge. Their work towards language-based, informal ontology building must be supported by easy-to-use workflows and supporting software, which we will demonstrate.
  • De Zubicaray, G. I., Acheson, D. J., & Hartsuiker, R. J. (Eds.). (2013). Mind what you say - general and specific mechanisms for monitoring in speech production [Research topic] [Special Issue]. Frontiers in Human Neuroscience. Retrieved from http://www.frontiersin.org/human_neuroscience/researchtopics/mind_what_you_say_-_general_an/1197.

    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.
  • Zwitserlood, I., Ozyurek, A., & Perniss, P. M. (2008). Annotation of sign and gesture cross-linguistically. In O. Crasborn, E. Efthimiou, T. Hanke, E. D. Thoutenhoofd, & I. Zwitserlood (Eds.), Construction and Exploitation of Sign Language Corpora. 3rd Workshop on the Representation and Processing of Sign Languages (pp. 185-190). Paris: ELDA.

    Abstract

    This paper discusses the construction of a cross-linguistic, bimodal corpus containing three modes of expression: expressions from two sign languages, speech and gestural expressions in two spoken languages and pantomimic expressions by users of two spoken languages who are requested to convey information without speaking. We discuss some problems and tentative solutions for the annotation of utterances expressing spatial information about referents in these three modes, suggesting a set of comparable codes for the description of both sign and gesture. Furthermore, we discuss the processing of entered annotations in ELAN, e.g. relating descriptive annotations to analytic annotations in all three modes and performing relational searches across annotations on different tiers.

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