Towards real life applications in emotion recognition: Comparing different databases, feature sets, and reinforcement methods for recognizing emotions from speech

Abstract

In this paper different kinds of emotional speech corpora are compared in terms of speech acquisition (acted speech vs. elicited speech), utterance length and similarity to spontaneous speech. Feature selection is applied to find an optimal feature set and to examine the correlation of different kinds of features to dimensions in the emotional space. The influence of different feature sets is evaluated. To cope with environmental conditions and to get a robust application, effects related to energy and additive noise are analyzed.