Publications

Displaying 201 - 217 of 217
  • 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. (1998). Biri. München: Lincom Europa.

    Abstract

    This work presents a salvage grammar of the Biri language of Eastern Central Queensland, a Pama-Nyungan language belonging to the large Maric subgroup. As the language is no longer used, the grammatical description is based on old written sources and on recordings made by linguists in the 1960s and 1970s. Biri is in many ways typical of the Pama-Nyungan languages of Southern Queensland. It has split case marking systems, marking nouns according to an ergative/absolutive system and pronouns according to a nominative/accusative system. Unusually for its area, Biri also has bound pronouns on its verb, cross-referencing the person, number and case of core participants. As far as it is possible, the grammatical discussion is ‘theory neutral’. The first four chapters deal with the phonology, morphology, and syntax of the language. The last two chapters contain a substantial discussion of Biri’s place in the Pama-Nyungan family. In chapter 6 the numerous dialects of the Biri language are discussed. In chapter 7 the close linguistic relationship between Biri and the surrounding languages is examined.
  • Terrill, A. (2004). Coordination in Lavukaleve. In M. Haspelmath (Ed.), Coordinating Constructions. (pp. 427-443). Amsterdam: John Benjamins.
  • 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 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 Berkum, J. J. A. (2004). Sentence comprehension in a wider discourse: Can we use ERPs to keep track of things? In M. Carreiras, Jr., & C. Clifton (Eds.), The on-line study of sentence comprehension: eyetracking, ERPs and beyond (pp. 229-270). New York: Psychology Press.
  • 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. (2004). Die Gesetze des Geistes sind metrisch: Hölderlin und die Sprachproduktion. In H. Schwarz (Ed.), Fenster zur Welt: Deutsch als Fremdsprachenphilologie (pp. 439-460). München: Iudicium.
  • Wilkins, D. (1993). Route Description Elicitation. In S. C. Levinson (Ed.), Cognition and space kit 1.0 (pp. 15-28). Nijmegen: Max Planck Institute for Psycholinguistics. doi:10.17617/2.3513141.

    Abstract

    When we want to describe a path through space, but do not share a common perceptual field with a conversation partner, language has to work doubly hard. This task investigates how people communicate the navigation of space in the absence of shared visual cues, as well as collecting data on motion verbs and the roles of symmetry and landmarks in route description. Two speakers (separated by a curtain or other barrier) are each given a model of a landscape, and one participant describes standard routes through this landscape for the other to match.
  • Wilkins, D., & Hill, D. (1993). Preliminary 'Come' and 'Go' Questionnaire. In S. C. Levinson (Ed.), Cognition and space kit 1.0 (pp. 29-46). Nijmegen: Max Planck Institute for Psycholinguistics. doi:10.17617/2.3513125.

    Abstract

    The encoding of apparently ‘simple’ movement concepts such as ‘COME’ and ‘GO’ can differ widely across languages (e.g., in regard to specifying direction of motion relative to the speaker). This questionnaire is used to identify the range of use of basic motion verbs in a language, and investigate semantic parameters that are involved in high frequency ‘COME’ and ‘GO’-like terms.
  • Zeshan, U. (2004). Basic English course taught in Indian Sign Language (Ali Yavar Young National Institute for Hearing Handicapped, Ed.). National Institute for the Hearing Handicapped: Mumbai.
  • 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.
  • Zinken, J., Rossi, G., & Reddy, V. (2020). Doing more than expected: Thanking recognizes another's agency in providing assistance. In C. Taleghani-Nikazm, E. Betz, & P. Golato (Eds.), Mobilizing others: Grammar and lexis within larger activities (pp. 253-278). Amsterdam: John Benjamins.

    Abstract

    In informal interaction, speakers rarely thank a person who has complied with a request. Examining data from British English, German, Italian, Polish, and Telugu, we ask when speakers do thank after compliance. The results show that thanking treats the other’s assistance as going beyond what could be taken for granted in the circumstances. Coupled with the rareness of thanking after requests, this suggests that cooperation is to a great extent governed by expectations of helpfulness, which can be long-standing, or built over the course of a particular interaction. The higher frequency of thanking in some languages (such as English or Italian) suggests that cultures differ in the importance they place on recognizing the other’s agency in doing as requested.
  • 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.

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