Publications

Displaying 201 - 233 of 233
  • Seuren, P. A. M. (2006). Multivalued logics. In K. Brown (Ed.), Encyclopedia of Language and Linguistics (vol. 8) (pp. 387-390). Amsterdam: Elsevier.

    Abstract

    The widely prevailing view that standard bivalent logic is the only possible sound logical system, imposed by metaphysical necessity, has been shattered by the development of multivalent logics during the 20th century. It is now clear that standard bivalent logic is merely the minimal representative of a wide variety of viable logics with any number of truth values. These viable logics can be subdivided into families. In this article, the Kleene family and the PPCn family are subjected to special examination, as they appear to be most relevant for the study of the logical properties of human language.
  • Seuren, P. A. M. (1988). Lexical meaning and presupposition. In W. Hüllen, & R. Schulze (Eds.), Understanding the lexicon: Meaning, sense and world knowledge in lexical semantics (pp. 170-187). Tübingen: Niemeyer.
  • Seuren, P. A. M. (1989). Notes on reflexivity. In F. J. Heyvaert, & F. Steurs (Eds.), Worlds behind words: Essays in honour of Prof. Dr. F.G. Droste on the occasion of his sixtieth birthday (pp. 85-95). Leuven: Leuven University Press.
  • Seuren, P. A. M. (1998). Towards a discourse-semantic account of donkey anaphora. In S. Botley, & T. McEnery (Eds.), New Approaches to Discourse Anaphora: Proceedings of the Second Colloquium on Discourse Anaphora and Anaphor Resolution (DAARC2) (pp. 212-220). Lancaster: Universiy Centre for Computer Corpus Research on Language, Lancaster University.
  • Sjerps, M. J., & Chang, E. F. (2019). The cortical processing of speech sounds in the temporal lobe. In P. Hagoort (Ed.), Human language: From genes and brain to behavior (pp. 361-379). Cambridge, MA: MIT Press.
  • Skiba, R. (1988). Computer analysis of language data using the data transformation program TEXTWOLF in conjunction with a database system. In U. Jung (Ed.), Computers in applied linguistics and language teaching (pp. 155-159). Frankfurt am Main: Peter Lang.
  • Skiba, R. (2006). Computeranalyse/Computer Analysis. In U. Amon, N. Dittmar, K. Mattheier, & P. Trudgill (Eds.), Sociolinguistics: An international handbook of the science of language and society [2nd completely revised and extended edition] (pp. 1187-1197). Berlin, New York: de Gruyter.
  • Skiba, R. (1988). Computerunterstützte Analyse von sprachlichen Daten mit Hilfe des Datenumwandlungsprogramms TextWolf in Kombination mit einem Datenbanksystem. In B. Spillner (Ed.), Angewandte Linguistik und Computer (pp. 86-88). Tübingen: Gunter Narr.
  • Skiba, R. (1989). Funktionale Beschreibung von Lernervarietäten: Das Berliner Projekt P-MoLL. In N. Reiter (Ed.), Sprechen und Hören: Akte des 23. Linguistischen Kolloquiums, Berlin (pp. 181-191). Tübingen: Niemeyer.
  • Slobin, D. I. (2002). Cognitive and communicative consequences of linguistic diversity. In S. Strömqvist (Ed.), The diversity of languages and language learning (pp. 7-23). Lund, Sweden: Lund University, Centre for Languages and Literature.
  • Stassen, H., & Levelt, W. J. M. (1976). Systemen, automaten en grammatica's. In J. Michon, E. Eijkman, & L. De Klerk (Eds.), Handboek der psychonomie (pp. 100-127). Deventer: Van Loghum Slaterus.
  • Stivers, T. (2006). Treatment decisions: negotiations between doctors and parents in acute care encounters. In J. Heritage, & D. W. Maynard (Eds.), Communication in medical care: Interaction between primary care physicians and patients (pp. 279-312). Cambridge: Cambridge University Press.
  • Stolker, C. J. J. M., & Poletiek, F. H. (1998). Smartengeld - Wat zijn we eigenlijk aan het doen? Naar een juridische en psychologische evaluatie. In F. Stadermann (Ed.), Bewijs en letselschade (pp. 71-86). Lelystad, The Netherlands: Koninklijke Vermande.
  • Suppes, P., Böttner, M., & Liang, L. (1998). Machine Learning of Physics Word Problems: A Preliminary Report. In A. Aliseda, R. van Glabbeek, & D. Westerståhl (Eds.), Computing Natural Language (pp. 141-154). Stanford, CA, USA: CSLI Publications.
  • Terrill, A., & Dunn, M. (2006). Semantic transference: Two preliminary case studies from the Solomon Islands. In C. Lefebvre, L. White, & C. Jourdan (Eds.), L2 acquisition and Creole genesis: Dialogues (pp. 67-85). Amsterdam: Benjamins.
  • Terrill, A. (2006). Central Solomon languages. In K. Brown (Ed.), Encyclopedia of language and linguistics (vol. 2) (pp. 279-280). Amsterdam: Elsevier.

    Abstract

    The Papuan languages of the central Solomon Islands are a negatively defined areal grouping: They are those four or possibly five languages in the central Solomon Islands that do not belong to the Austronesian family. Bilua (Vella Lavella), Touo (Rendova), Lavukaleve (Russell Islands), Savosavo (Savo Island) and possibly Kazukuru (New Georgia) have been identified as non-Austronesian since the early 20th century. However, their affiliations both to each other and to other languages still remain a mystery. Heterogeneous and until recently largely undescribed, they present an interesting departure from what is known both of Austronesian languages in the region and of the Papuan languages of the mainland of New Guinea.
  • Thomassen, A., & Kempen, G. (1976). Geheugen. In J. A. Michon, E. Eijkman, & L. F. De Klerk (Eds.), Handboek der Psychonomie (pp. 354-387). Deventer: Van Loghum Slaterus.
  • Thomaz, A. L., Lieven, E., Cakmak, M., Chai, J. Y., Garrod, S., Gray, W. D., Levinson, S. C., Paiva, A., & Russwinkel, N. (2019). Interaction for task instruction and learning. In K. A. Gluck, & J. E. Laird (Eds.), Interactive task learning: Humans, robots, and agents acquiring new tasks through natural interactions (pp. 91-110). Cambridge, MA: MIT Press.
  • Van Staden, M., Bowerman, M., & Verhelst, M. (2006). Some properties of spatial description in Dutch. In S. C. Levinson, & D. Wilkins (Eds.), Grammars of Space (pp. 475-511). Cambridge: Cambridge University Press.
  • Van Berkum, J. J. A., & Nieuwland, M. S. (2019). A cognitive neuroscience perspective on language comprehension in context. In P. Hagoort (Ed.), Human language: From genes and brain to behavior (pp. 429-442). Cambridge, MA: MIT Press.
  • Van Geenhoven, V. (1998). On the Argument Structure of some Noun Incorporating Verbs in West Greenlandic. In M. Butt, & W. Geuder (Eds.), The Projection of Arguments - Lexical and Compositional Factors (pp. 225-263). Stanford, CA, USA: CSLI Publications.
  • Van Valin Jr., R. D. (1998). The acquisition of WH-questions and the mechanisms of language acquisition. In M. Tomasello (Ed.), The new psychology of language: Cognitive and functional approaches to language structure (pp. 221-249). Mahwah, New Jersey: Erlbaum.
  • Van Valin Jr., R. D. (2006). Some universals of verb semantics. In R. Mairal, & J. Gil (Eds.), Linguistic universals (pp. 155-178). Cambridge: Cambridge University Press.
  • Van Valin Jr., R. D. (2006). Semantic macroroles and language processing. In I. Bornkessel, M. Schlesewsky, B. Comrie, & A. Friederici (Eds.), Semantic role universals and argument linking: Theoretical, typological and psycho-/neurolinguistic perspectives (pp. 263-302). Berlin: Mouton de Gruyter.
  • Vernes, S. C. (2019). Neuromolecular approaches to the study of language. In P. Hagoort (Ed.), Human language: From genes and brain to behavior (pp. 577-593). Cambridge, MA: MIT Press.
  • Von Stutterheim, C., & Klein, W. (1989). Referential movement in descriptive and narrative discourse. In R. Dietrich, & C. F. Graumann (Eds.), Language processing in social context (pp. 39-76). Amsterdam: Elsevier.
  • Weissenborn, J. (1988). Von der demonstratio ad oculos zur Deixis am Phantasma. Die Entwicklung der lokalen Referenz bei Kindern. In Karl Bühler's Theory of Language. Proceedings of the Conference held at Kirchberg, August 26, 1984 and Essen, November 21–24, 1984 (pp. 257-276). Amsterdam: Benjamins.
  • 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.
  • Zeshan, U. (2006). Sign language of the world. In K. Brown (Ed.), Encyclopedia of language and linguistics (vol. 11) (pp. 358-365). Amsterdam: Elsevier.

    Abstract

    Although sign language-using communities exist in all areas of the world, few sign languages have been documented in detail. Sign languages occur in a variety of sociocultural contexts, ranging from sign languages used in closed village communities to officially recognized national sign languages. They may be grouped into language families on historical grounds or may participate in various language contact situations. Systematic cross-linguistic comparison reveals both significant structural similarities and important typological differences between sign languages. Focusing on information from non-Western countries, this article provides an overview of the sign languages of the world.
  • Zhang, Y., Chen, C.-h., & Yu, C. (2019). Mechanisms of cross-situational learning: Behavioral and computational evidence. In Advances in Child Development and Behavior; vol. 56 (pp. 37-63).

    Abstract

    Word learning happens in everyday contexts with many words and many potential referents for those words in view at the same time. It is challenging for young learners to find the correct referent upon hearing an unknown word at the moment. This problem of referential uncertainty has been deemed as the crux of early word learning (Quine, 1960). Recent empirical and computational studies have found support for a statistical solution to the problem termed cross-situational learning. Cross-situational learning allows learners to acquire word meanings across multiple exposures, despite each individual exposure is referentially uncertain. Recent empirical research shows that infants, children and adults rely on cross-situational learning to learn new words (Smith & Yu, 2008; Suanda, Mugwanya, & Namy, 2014; Yu & Smith, 2007). However, researchers have found evidence supporting two very different theoretical accounts of learning mechanisms: Hypothesis Testing (Gleitman, Cassidy, Nappa, Papafragou, & Trueswell, 2005; Markman, 1992) and Associative Learning (Frank, Goodman, & Tenenbaum, 2009; Yu & Smith, 2007). Hypothesis Testing is generally characterized as a form of learning in which a coherent hypothesis regarding a specific word-object mapping is formed often in conceptually constrained ways. The hypothesis will then be either accepted or rejected with additional evidence. However, proponents of the Associative Learning framework often characterize learning as aggregating information over time through implicit associative mechanisms. A learner acquires the meaning of a word when the association between the word and the referent becomes relatively strong. In this chapter, we consider these two psychological theories in the context of cross-situational word-referent learning. By reviewing recent empirical and cognitive modeling studies, our goal is to deepen our understanding of the underlying word learning mechanisms by examining and comparing the two theoretical learning accounts.
  • Zuidema, W., & Fitz, H. (2019). Key issues and future directions: Models of human language and speech processing. In P. Hagoort (Ed.), Human language: From genes and brain to behavior (pp. 353-358). Cambridge, MA: MIT Press.
  • Zwitserlood, I., & Van Gijn, I. (2006). Agreement phenomena in Sign Language of the Netherlands. In P. Ackema (Ed.), Arguments and Agreement (pp. 195-229). Oxford: Oxford University Press.
  • 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.

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