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  1. Quantifying the Beauty of Words: A Neurocognitive Poetics Perspective.Arthur M. Jacobs - 2017 - Frontiers in Human Neuroscience 11.
  • Lexical Predictability During Natural Reading: Effects of Surprisal and Entropy Reduction.Matthew W. Lowder, Wonil Choi, Fernanda Ferreira & John M. Henderson - 2018 - Cognitive Science 42 (S4):1166-1183.
    What are the effects of word-by-word predictability on sentence processing times during the natural reading of a text? Although information complexity metrics such as surprisal and entropy reduction have been useful in addressing this question, these metrics tend to be estimated using computational language models, which require some degree of commitment to a particular theory of language processing. Taking a different approach, this study implemented a large-scale cumulative cloze task to collect word-by-word predictability data for 40 passages and compute surprisal (...)
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  • Using Statistical Models of Morphology in the Search for Optimal Units of Representation in the Human Mental Lexicon.Sami Virpioja, Minna Lehtonen, Annika Hultén, Henna Kivikari, Riitta Salmelin & Krista Lagus - 2018 - Cognitive Science 42 (3):939-973.
    Determining optimal units of representing morphologically complex words in the mental lexicon is a central question in psycholinguistics. Here, we utilize advances in computational sciences to study human morphological processing using statistical models of morphology, particularly the unsupervised Morfessor model that works on the principle of optimization. The aim was to see what kind of model structure corresponds best to human word recognition costs for multimorphemic Finnish nouns: a model incorporating units resembling linguistically defined morphemes, a whole-word model, or a (...)
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  • The Influence of Visual Uncertainty on Word Surprisal and Processing Effort.Christine S. Ankener, Mirjana Sekicki & Maria Staudte - 2018 - Frontiers in Psychology 9.
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