Publications

Displaying 301 - 322 of 322
  • 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.
  • Trabasso, T., & Ozyurek, A. (1997). Communicating evaluation in narrative understanding. In T. Givon (Ed.), Conversation: Cognitive, communicative and social perspectives (pp. 268-302). Philadelphia, PA: Benjamins.
  • Trilsbeek, P., & Wittenburg, P. (2007). "Los acervos lingüísticos digitales y sus desafíos". In J. Haviland, & F. Farfán (Eds.), Bases de la documentacíon lingüística (pp. 359-385). Mexico: Instituto Nacional de Lenguas Indígenas.

    Abstract

    This chapter describes the challenges that modern digital language archives are faced with. One essential aspect of such an archive is to have a rich metadata catalog such that the archived resources can be easily discovered. The challenge of the archive is to obtain these rich metadata descriptions from the depositors without creating too much overhead for them. The rapid changes in storage technology, file formats and encoding standards make it difficult to build a long-lasting repository, therefore archives need to be set up in such a way that a straightforward and automated migration process to newer technology is possible whenever certain technology becomes obsolete. Other problems arise from the fact that there are many different groups of users of the archive, each of them with their own specific expectations and demands. Often conflicts exist between the requirements for different purposes of the archive, e.g. between long-term preservation of the data versus direct access to the resources via the web. The task of the archive is to come up with a technical solution that works well for most usage scenarios.
  • Tufvesson, S. (2007). Expressives. In A. Majid (Ed.), Field Manual Volume 10 (pp. 53-58). Nijmegen: Max Planck Institute for Psycholinguistics. doi:10.17617/2.492919.
  • 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 Alphen, P. M. (2007). Prevoicing in Dutch initial plosives: Production, perception, and word recognition. In J. van de Weijer, & E. van der Torre (Eds.), Voicing in Dutch (pp. 99-124). Amsterdam: Benjamins.

    Abstract

    Prevoicing is the presence of vocal fold vibration during the closure of initial voiced plosives (negative VOT). The presence or absence of prevoicing is generally used to describe the voicing distinction in Dutch initial plosives. However, a phonetic study showed that prevoicing is frequently absent in Dutch. This article discusses the role of prevoicing in the production and perception of Dutch plosives. Furthermore, two cross-modal priming experiments are presented that examined the effect of prevoicing variation on word recognition. Both experiments showed no difference between primes with 12, 6 or 0 periods of prevoicing, even though a third experiment indicated that listeners could discriminate these words. These results are discussed in light of another priming experiment that did show an effect of the absence of prevoicing, but only when primes had a voiceless word competitor. Phonetic detail appears to influence lexical access only when it helps to distinguish between lexical candidates.
  • Van Berkum, J. J. A., Hijne, H., De Jong, T., Van Joolingen, W. R., & Njoo, M. (1995). Characterizing the application of computer simulations in education: Instructional criteria. In A. Ram, & D. B. Leake (Eds.), Goal-driven learning (pp. 381-392). Cambridge, M: MIT Press.
  • 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 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 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.
  • 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.
  • Van Valin Jr., R. D. (1995). Toward a functionalist account of so-called ‘extraction constraints’. In B. Devriendt (Ed.), Complex structures: A functionalist perspective (pp. 29-60). Berlin: Mouton de Gruyter.
  • Verdonschot, R. G., & Tamaoka, K. (Eds.). (2015). The production of speech sounds across languages [Special Issue]. Japanese Psychological Research, 57(1).
  • 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. (1995). Towards a Socio-Cultural Profile of the Communities We Work With. In D. Wilkins (Ed.), Extensions of space and beyond: manual for field elicitation for the 1995 field season (pp. 70-79). Nijmegen: Max Planck Institute for Psycholinguistics. doi:10.17617/2.3513481.

    Abstract

    Field data are drawn from a particular speech community at a certain place and time. The intent of this survey is to enrich understanding of the various socio-cultural contexts in which linguistic and “cognitive” data may have been collected, so that we can explore the role which societal, cultural and contextual factors may play in this material. The questionnaire gives guidelines concerning types of ethnographic information that are important to cross-cultural and cross-linguistic enquiry, and will be especially useful to researchers who do not have specialised training in anthropology.
  • Wilkins, D., Pederson, E., & Levinson, S. C. (1995). Background questions for the "enter"/"exit" research. In D. Wilkins (Ed.), Extensions of space and beyond: manual for field elicitation for the 1995 field season (pp. 14-16). Nijmegen: Max Planck Institute for Psycholinguistics. doi:10.17617/2.3003935.

    Abstract

    How do languages encode different kinds of movement, and what features do people pay attention to when describing motion events? This document outlines topics concerning the investigation of “enter” and “exit” events. It helps contextualise research tasks that examine this domain (see 'Motion Elicitation' and 'Enter/Exit animation') and gives some pointers about what other questions can be explored.
  • Wilkins, D., Kita, S., & Enfield, N. J. (2007). 'Ethnography of pointing' - field worker's guide. In A. Majid (Ed.), Field Manual Volume 10 (pp. 89-95). Nijmegen: Max Planck Institute for Psycholinguistics. doi:10.17617/2.492922.

    Abstract

    Pointing gestures are recognised to be a primary manifestation of human social cognition and communicative capacity. The goal of this task is to collect empirical descriptions of pointing practices in different cultural settings.
  • Wilkins, D. (1995). Motion elicitation: "moving 'in(to)'" and "moving 'out (of)'". In D. Wilkins (Ed.), Extensions of space and beyond: manual for field elicitation for the 1995 field season (pp. 4-12). Nijmegen: Max Planck Institute for Psycholinguistics. doi:10.17617/2.3003391.

    Abstract

    How do languages encode different kinds of movement, and what features do people pay attention to when describing motion events? This task investigates the expression of “enter” and “exit” activities, that is, events involving motion in(to) and motion out (of) container-like items. The researcher first uses particular stimuli (a ball, a cup, rice, etc.) to elicit descriptions of enter/exit events from one consultant, and then asks another consultant to demonstrate the event based on these descriptions. See also the related entries Enter/Exit Animation and Background Questions for Enter/Exit Research.
  • 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.
  • 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.

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