Publications

Displaying 201 - 221 of 221
  • Sumer, B., Zwitserlood, I., Perniss, P., & Ozyurek, A. (2016). Yer Bildiren İfadelerin Türkçe ve Türk İşaret Dili’nde (TİD) Çocuklar Tarafından Edinimi [The acqusition of spatial relations by children in Turkish and Turkish Sign Language (TID)]. In E. Arik (Ed.), Ellerle Konuşmak: Türk İşaret Dili Araştırmaları [Speaking with hands: Studies on Turkish Sign Language] (pp. 157-182). Istanbul: Koç University Press.
  • 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.
  • Ten Oever, S. (2016). How neuronal oscillations code for temporal statistics. PhD Thesis, Maastricht University, Maastricht, The Netherlands.
  • Todorova, L. (2021). Language bias in visually driven decisions: Computational neurophysiological mechanisms. PhD Thesis, Radboud University Nijmegen, Nijmegen.
  • Trompenaars, T. (2021). Bringing stories to life: Animacy in narrative and processing. PhD Thesis, Radboud University Nijmegen, Nijmegen.
  • Trujillo, J. P., Levinson, S. C., & Holler, J. (2021). Visual information in computer-mediated interaction matters: Investigating the association between the availability of gesture and turn transition timing in conversation. In M. Kurosu (Ed.), Human-Computer Interaction. Design and User Experience Case Studies. HCII 2021 (pp. 643-657). Cham: Springer. doi:10.1007/978-3-030-78468-3_44.

    Abstract

    Natural human interaction involves the fast-paced exchange of speaker turns. Crucially, if a next speaker waited with planning their turn until the current speaker was finished, language production models would predict much longer turn transition times than what we observe. Next speakers must therefore prepare their turn in parallel to listening. Visual signals likely play a role in this process, for example by helping the next speaker to process the ongoing utterance and thus prepare an appropriately-timed response.

    To understand how visual signals contribute to the timing of turn-taking, and to move beyond the mostly qualitative studies of gesture in conversation, we examined unconstrained, computer-mediated conversations between 20 pairs of participants while systematically manipulating speaker visibility. Using motion tracking and manual gesture annotation, we assessed 1) how visibility affected the timing of turn transitions, and 2) whether use of co-speech gestures and 3) the communicative kinematic features of these gestures were associated with changes in turn transition timing.

    We found that 1) decreased visibility was associated with less tightly timed turn transitions, and 2) the presence of gestures was associated with more tightly timed turn transitions across visibility conditions. Finally, 3) structural and salient kinematics contributed to gesture’s facilitatory effect on turn transition times.

    Our findings suggest that speaker visibility--and especially the presence and kinematic form of gestures--during conversation contributes to the temporal coordination of conversational turns in computer-mediated settings. Furthermore, our study demonstrates that it is possible to use naturalistic conversation and still obtain controlled results.
  • Tsoukala, C. (2021). Bilingual sentence production and code-switching: Neural network simulations. PhD Thesis, Radboud University Nijmegen, Nijmegen.
  • Van Dijk, C. N. (2021). Cross-linguistic influence during real-time sentence processing in bilingual children and adults. PhD Thesis, Raboud University Nijmegen, Nijmegen.
  • van der Burght, C. L. (2021). The central contribution of prosody to sentence processing: Evidence from behavioural and neuroimaging studies. PhD Thesis, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig.
  • Van Paridon, J. (2021). Speaking while listening: Language processing in speech shadowing and translation. PhD Thesis, Radboud University Nijmegen, Nijmegen.
  • Van Valin Jr., R. D. (2016). An overview of information structure in three Amazonian languages. In M. Fernandez-Vest, & R. D. Van Valin Jr. (Eds.), Information structure and spoken language from a cross-linguistic perspective (pp. 77-92). Berlin: Mouton de Gruyter.
  • 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 Rijswijk, R. (2016). The strength of a weaker first language: Language production and comprehension by Turkish heritage speakers in the Netherlands. PhD Thesis, Radboud University, Nijmegen, The Netherlands.
  • Verhoef, E. (2021). Why do we change how we speak? Multivariate genetic analyses of language and related traits across development and disorder. PhD Thesis, Radboud University Nijmegen, Nijmegen.
  • Viebahn, M. (2016). Acoustic reduction in spoken-word processing: Distributional, syntactic, morphosyntactic, and orthographic effects. PhD Thesis, Radboud University Nijmegen, Nijmegen.
  • Weissenborn, J. (1986). Learning how to become an interlocutor. The verbal negotiation of common frames of reference and actions in dyads of 7–14 year old children. In J. Cook-Gumperz, W. A. Corsaro, & J. Streeck (Eds.), Children's worlds and children's language (pp. 377-404). Berlin: Mouton de Gruyter.
  • 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.
  • Wnuk, E. (2016). Semantic specificity of perception verbs in Maniq. PhD Thesis, Radboud University Nijmegen, Nijmegen.
  • Zavala, R. (2000). Multiple classifier systems in Akatek (Mayan). In G. Senft (Ed.), Systems of nominal classification (pp. 114-146). Cambridge 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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