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All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year Sort by creator [A → Z]' creator [Z → A]' publishing year ↑ (asc)' publishing year ↓ (desc)' title [A → Z]' title [Z → A]' Simple Search Hits 1 – 2 of 2 1 Word Probability Re-Estimation Using Topic Modeling and Lexical Decision Data ... 43rd Annual Meeting of the Cognitive Science Society 2021; Keuleers, Emmanuel. - : Underline Science Inc., 2021 Abstract: Two assumptions of psycholinguistic research are that text corpora can be used as a proxy of the language that people have been exposed to and that the reaction time with which people recognize words decreases with the probability (or frequency) of the words in a corpus. We propose a method that produces topic-specific word probabilities from a text corpus using latent Dirichlet allocation, then combines them to fit lexical decision reaction times and re-estimates word probabilities. We evaluated how well independent lexical decision reaction times could be predicted from re-estimated word probabilities compared to original probabilities, using independent lexical decision data. In an experiment designed to prove the concept, the re-estimated word frequency model explained up to 9.6% of additional variability in reaction times on group level and up to 2.9% on level of individual participants. ... Keyword: Applied Linguistics; Cognitive Linguistics; Cognitive Science; Computational Intelligence; Computational Linguistics; Psycholinguistics URL: https://dx.doi.org/10.48448/521q-x620 https://underline.io/lecture/26766-word-probability-re-estimation-using-topic-modeling-and-lexical-decision-data BASE Hide details 2 Word Probability Re-Estimation Using Topic Modeling and Lexical Decision Data ... 43rd Annual Meeting of the Cognitive Science Society 2021; Keuleers, Emmanuel. - : Underline Science Inc., 2021 BASE Show details

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