Exploiting a Vowel Based Approach for Acted Emotion Recognition

Authors:
Fabien Ringeval;Mohamed Chetouani
Affiliations:
Université Pierre et Marie Curie --- Paris 6, Institut des Systèmes Intelligents et de Robotique, Ivry sur Seine, France 94200;Université Pierre et Marie Curie --- Paris 6, Institut des Systèmes Intelligents et de Robotique, Ivry sur Seine, France 94200
Venue:
Verbal and Nonverbal Features of Human-Human and Human-Machine Interaction
Year:
2008

Citing 6
Cited 1

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Abstract

This paper is dedicated to the description and the study of a new feature extraction approach for emotion recognition. Our contribution is based on the extraction and the characterization of phonemic units such as vowels and consonants, which are provided by a pseudo-phonetic speech segmentation phase combined with a vowel detector. The segmentation algorithm is evaluated on both emotional (Berlin) and non-emotional (TIMIT, NTIMIT) databases. Concerning the emotion recognition task, we propose to extract MFCC acoustic features from these pseudo-phonetic segments (vowels, consonants) and we compare this approach with traditional voice and unvoiced segments. The classification is achieved by the well-known k-nn classifier (k nearest neighbors) on the Berlin corpus.