Emotion Recognition with Poincare Mapping of Voiced-Speech Segments of Utterances

Authors:
Krzysztof Ślot;Jaroslaw Cichosz;Lukasz Bronakowski
Affiliations:
Institute of Electronics, Technical University of Lodz, Lodz, Poland 90-924;Institute of Electronics, Technical University of Lodz, Lodz, Poland 90-924;Institute of Electronics, Technical University of Lodz, Lodz, Poland 90-924
Venue:
ICAISC '08 Proceedings of the 9th international conference on Artificial Intelligence and Soft Computing
Year:
2006

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Abstract

The following paper introduces a set of novel descriptors of emotional speech, which allows for a significant increase in emotion classification performance. The proposed characteristics - statistical properties of Poincare Maps, derived for voiced-speech segments of utterances - are used in recognition in combinations with a variety of both commonly used and some other, original descriptors of emotional speech. The introduced features proved to provide useful information into a classification process. Emotion recognition is performed using binary decision trees, which perform extraction of different emotions at consecutive decision levels. Classification rates for the considered six-category problem, which involved anger, boredom, joy, fear, neutral and sadness, are at the level up to 79% for both speaker-dependent and speaker-independent cases.