Publications

Displaying 201 - 225 of 225
  • Skiba, R. (1993). Funktionale Analyse des Spracherwerbs einer polnischen Deutschlernerin. In A. Katny (Ed.), Beiträge zur Sprachwissenschaft, Psycho- und Soziolinguistik: Probleme des Deutschen als Mutter-, Fremd- und Zweitsprache (pp. 201-225). Rzeszów: WSP.
  • Skiba, R. (1993). Modal verbs and their syntactical characteristics in elementary learner varieties. In N. Dittmar, & A. Reich (Eds.), Modality in language acquisition (pp. 247-260). Berlin: Walter de Gruyter.
  • Skiba, R. (1990). Steinbruch-Datenbanken: Materialien für „Deutsch als Zweitsprache für Kinder und Jugendliche" und „Deutsch als Fachsprache". In Lehr- und Lernmittel-Datenbanken für den Fremdsprachenunterricht (pp. 15-20). Zürich: Eurocentres - Learning Service.
  • De Sousa, H., Langella, F., & Enfield, N. J. (2015). Temperature terms in Lao, Southern Zhuang, Southern Pinghua and Cantonese. In M. Koptjevskaja-Tamm (Ed.), The linguistics of temperature (pp. 594-638). Amsterdam: Benjamins.
  • 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.
  • 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.
  • Trilsbeek, P., & Wittenburg, P. (2005). Archiving challenges. In J. Gippert, N. Himmelmann, & U. Mosel (Eds.), Essentials of language documentation (pp. 311-335). Berlin: Mouton de Gruyter.
  • Udden, J., & Schoffelen, J.-M. (2015). Mother of all Unification Studies (MOUS). In A. E. Konopka (Ed.), Research Report 2013 | 2014 (pp. 21-22). Nijmegen: Max Planck Institute for Psycholinguistics. doi:10.17617/2.2236748.
  • 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 Heugten, M., Bergmann, C., & Cristia, A. (2015). The Effects of Talker Voice and Accent on Young Children's Speech Perception. In S. Fuchs, D. Pape, C. Petrone, & P. Perrier (Eds.), Individual Differences in Speech Production and Perception (pp. 57-88). Bern: Peter Lang.

    Abstract

    Within the first few years of life, children acquire many of the building blocks of their native language. This not only involves knowledge about the linguistic structure of spoken language, but also knowledge about the way in which this linguistic structure surfaces in their speech input. In this chapter, we review how infants and toddlers cope with differences between speakers and accents. Within the context of milestones in early speech perception, we examine how voice and accent characteristics are integrated during language processing, looking closely at the advantages and disadvantages of speaker and accent familiarity, surface-level deviation between two utterances, variability in the input, and prior speaker exposure. We conclude that although deviation from the child’s standard can complicate speech perception early in life, young listeners can overcome these additional challenges. This suggests that early spoken language processing is flexible and adaptive to the listening situation at hand.
  • 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.
  • 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.
  • 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.
  • 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.
  • Zeshan, U. (2005). Sign languages. In M. Haspelmath, M. S. Dryer, D. Gil, & B. Comrie (Eds.), The world atlas of language structures (pp. 558-559). Oxford: Oxford University Press.
  • Zeshan, U. (2005). Question particles in sign languages. In M. Haspelmath, M. S. Dryer, D. Gil, & B. Comrie (Eds.), The world atlas of language structures (pp. 564-567). Oxford: Oxford University Press.
  • Zeshan, U., Pfau, R., & Aboh, E. (2005). When a wh-word is not a wh-word: the case of Indian sign language. In B. Tanmoy (Ed.), Yearbook of South Asian languages and linguistics 2005 (pp. 11-43). Berlin: Mouton de Gruyter.
  • Zeshan, U. (2005). Irregular negatives in sign languages. In M. Haspelmath, M. S. Dryer, D. Gil, & B. Comrie (Eds.), The world atlas of language structures (pp. 560-563). Oxford: Oxford University Press.
  • 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.

Share this page