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Communication Dans Un Congrès Année : 2018

Facial Expressions of Sentence Comprehension

Résumé

Understanding facial expressions allows access to one's intentional and affective states. Using the findings in psychology and neuroscience, in which physical behaviors of the face are linked to emotional states, this paper aims to study sentence comprehension shown by facial expressions. In our experiments, participants took part in a roughly 30-minute computer mediated task, where they were asked to answer either "true" or "false" to knowledge-based questions, then immediately given feedback of "correct" or "incorrect". Their faces, which were recorded during the task using the Kinect v2 device, are later used to identify the level of comprehension shown by their expressions. To achieve this, the SVM and Random Forest classifiers with facial appearance information extracted using a spatiotemporal local descriptor, named LPQ-TOP, are employed. Results of online sentence comprehension show that facial dynamics are promising to help understand cognitive states of the mind.
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Dates et versions

hal-02105450 , version 1 (21-04-2019)

Identifiants

  • HAL Id : hal-02105450 , version 1

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Cigdem Turan, Yixin Wang, Shun-Cheung Lai, Karl David Neergaard, Kin-Man Lam. Facial Expressions of Sentence Comprehension. IEEE International Conference on Digital Signal Processing (DSP2018), Special session : Signal Processing Education: Challenges and Technology Driven Opportunities, Nov 2018, Shanghai, China. ⟨hal-02105450⟩
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