Computational Linguistics & Phonetics Computational Linguistics & Phonetics Fachrichtung 4.7 Universität des Saarlandes
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Predictability and Anticipation - Information Theory meets Visual World


Much recent work has built on Information Theory to explain experimental results from psycholinguistics and statistical models of language. In sentence comprehension, for instance, a word conveys a certain amount of information (about what is to come next) and this amount is considered to be predictive of how much cognitive effort is required to process the word (Hale, 2006; Levy, 2008). What is predicted/anticipated to come next given a certain linguistic (and visual) context has been investigated using e.g. the Visual World Paradigm or the Cloze task. What cognitive effort is involved in processing a certain word has been measured empirically using e.g. reading times and ERPs, typically in linguistic context only. We will review the recent literature on these issues and discuss how the two approaches can be combined to assess the predicability of a certain word (in linguistic and visual context) and quantify the cognitive load (as an index of surprisal) associated with the word.


Course Information

Students will select one or two papers (e.g. from the selection given below) and present it to the audience. Presentations will be, depending on number of participants, approx. 50-60 mins (1 per slot). Presenters may have a feedback meeting for their slides 1-2 days before the presentation.
Short summaries of the relevant paper will be expected by all participants the night before the seminar.
Students may prepare a term paper for more credits.


If you would like to participate in this seminar, please sign up here until 22 October: piazza.com/uni-saarland.de/fall2017/sem02 !!


Literature
  • Predictability and Cognitive Load in Sentence Comprehension (Ling/CL)

    • Stefan Frank (2013). "Uncertainty Reduction as a Measure of Cognitive Load in Sentence Comprehension"
      Topics in Cognitive Science, 5, 475-494.

    • Frank, S. L., Otten, L. J., Galli, G., & Vigliocco, G. (2015). "The ERP response to the amount of information conveyed by words in sentences."
      Brain and language, 140, 1-11.

    • Kuperberg, G. R., & Jaeger, T. F. (2016). "What do we mean by prediction in language comprehension?"
      Language, cognition and neuroscience, 31(1), 32-59.

    • Maess, B., Mamashli, F., Obleser, J., Helle, L., & Friederici, A. D. (2016). "Prediction signatures in the brain: semantic pre-activation during language comprehension."
      Frontiers in human neuroscience, 10.

    • Linzen, T., & Jaeger, T. F. (2016). "Uncertainty and expectation in sentence processing: evidence from subcategorization distributions."
      Cognitive science, 40(6), 1382-1411.

    • Lowder, M., Choi, W., Ferreira, F., & Henderson, J. (unpub). "Lexical predictability during natural reading: Effects of surprisal and entropy reduction".
      psyarXiv.




  • Anticipation/Prediction in Sentence Comprehension (VWP)

    • Kamide, Y., Altmann, G. and Haywood, S. (2003). "The time-course of prediction in incremental sentence processing: Evidence from anticipatory eye movements"
      Psychonomic Bulletin and Review 12 (3), 453-459.

    • DeLong, K., Urbach T. and Kutas, M. (2005). "Probabilistic word pre-activation during language comprehension inferred from electrical brain activity"
      Natur Neuroscience 8 (8), 1117-1121.

    • Dahan, D. and Tanenhaus, M. (2005). "Looking at the rope when looking for the snake: Conceptually mediated eye movements during spoken-word recognition"
      Journal of Memory and Language (49), 133-156.

    • Huettig, F. and Altmann, G. (2005). "Word meaning and the control of eye fixation: semantic competitor effects and the visual world paradigm"
      Cognition 96 B23-B32.

    • Wang, H., HWang, A. and Pomplun, M. (2010). "Object Frequency and Predictability Effects on Eye Fixation Durations in Real-World Scene Viewing"
      Journal of Eye Movement Research 3 (3), 1-10.

    • Huettig, F. et al. (2011). "Language-mediated visual orienting behavior in low and high literates"
      Frontiers in Psychology 2, 1-14.

    • Rommers, J. et al. (2013). "The contents of predictions in sentence comprehension: Activation of the shape of objects before they are referred to"
      Neuropsychologia 51, 437-447.

    • Britt, A. et al. (2014). "Effect of repetition proportion on language-driven anticipatory eye movements"
      Acta Psychologica 145, 128-138.

    • Smith, A., Monaghan, P., & Huettig, F. (2014). "A comprehensive model of spoken word recognition must be multimodal: Evidence from studies of language-mediated visual attention"
      Proceedings of the 36th Annual Meeting of the Cognitive Science Society (CogSci 2014).

    • DeLong, K., Quante L. and Kutas, M. (2014). "Predictability, plausibility, and two late ERP positivities during written sentence comprehension"
      Neuropsychologia 61, 150-162.

    • Rommers, J. et al. (2015). "Verbal and nonverbal predictors of language-mediated anticipatory eye movements"
      Atten Percept Psychophys 77, 720-730.

    • Wlotko, E. and Federmeier, K. (2015). "Time for prediction? The effect of presentation rate on predictive sentence comprehension during word-by-word reading"
      Cortex, p. 1-13.




  • Anticipation and Cognitive Load (VWP)

    • Demberg, V. and Sayeed, A. (2016). "The Index of Cognitive Activity as a Measure of Linguistic Processing"
      Plos One.

    • Ankener, C. and Sekicki, M. (unpub). "Situated Surprisal"