Which prosodic features contribute to the recognition of dramatic attitudes?

Adela Barbulescu 1, 2 Rémi Ronfard 3 Gérard Bailly 1
1 GIPSA-CRISSP - CRISSP
GIPSA-DPC - Département Parole et Cognition
3 IMAGINE - Intuitive Modeling and Animation for Interactive Graphics & Narrative Environments
Inria Grenoble - Rhône-Alpes, LJK - Laboratoire Jean Kuntzmann, INPG - Institut National Polytechnique de Grenoble
Abstract : In this work we explore the capability of audiovisual prosodic features (such as fundamental frequency, head motion or facial expressions) to discriminate among different dramatic attitudes. We extract the audiovisual parameters from an acted corpus of attitudes and structure them as frame, syllable and sentence-level features. Using Linear Discriminant Analysis classifiers, we show that prosodic features present a higher discriminating rate at sentence-level. This finding is confirmed by the perceptual evaluation results of audio and/or visual stimuli obtained from the recorded attitudes.
Type de document :
Article dans une revue
Speech Communication, Elsevier : North-Holland, 2017, 95, pp.78-86. 〈10.1016/j.specom.2017.07.003〉
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Contributeur : Rémi Ronfard <>
Soumis le : mercredi 22 novembre 2017 - 13:14:37
Dernière modification le : jeudi 11 janvier 2018 - 06:27:21

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Adela Barbulescu, Rémi Ronfard, Gérard Bailly. Which prosodic features contribute to the recognition of dramatic attitudes?. Speech Communication, Elsevier : North-Holland, 2017, 95, pp.78-86. 〈10.1016/j.specom.2017.07.003〉. 〈hal-01643330〉

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