Dataset Information

Hidden Semi-Markov Models to Segment Reading Phases from Eye Movements.

ABSTRACT: Our objective is to analyze scanpaths acquired through participants achieving a reading task aiming at answering a binary question: Is the text related or not to some given target topic? We propose a data-driven method based on hidden semi-Markov chains to segment scanpaths into phases deduced from the model states, which are shown to represent different cognitive strategies: normal reading, fast reading, information search, and slow confirmation. These phases were confirmed using different external covariates, among which semantic information extracted from texts. Analyses highlighted some strong preference of specific participants for specific strategies and more globally, large individual variability in eye-movement characteristics, as accounted for by random effects. As a perspective, the possibility of improving reading models by accounting for possible heterogeneity sources during reading is discussed.

SUBMITTER: Olivier B

PROVIDER: S-EPMC10292930 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature

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Hidden Semi-Markov Models to Segment Reading Phases from Eye Movements.

Olivier Brice B Guérin-Dugué Anne A Durand Jean-Baptiste JB

Journal of eye movement research 20220930 4

Our objective is to analyze scanpaths acquired through participants achieving a reading task aiming at answering a binary question: Is the text related or not to some given target topic? We propose a data-driven method based on hidden semi-Markov chains to segment scanpaths into phases deduced from the model states, which are shown to represent different cognitive strategies: normal reading, fast reading, information search, and slow confirmation. These phases were confirmed using different exte ...[more]

PMID: 37377767

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Dataset Information

Hidden Semi-Markov Models to Segment Reading Phases from Eye Movements.

Publications

Hidden Semi-Markov Models to Segment Reading Phases from Eye Movements.

Similar Datasets

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