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Time-Scale Feature Extractions for Emotional Speech Characterization
2009
Cognitive Computation
Emotional speech characterization is an important issue for the understanding of interaction. This article discusses the time-scale analysis problem in feature extraction for emotional speech processing. We describe a computational framework for combining segmental and supra-segmental features for emotional speech detection. The statistical fusion is based on the estimation of local a posteriori class probabilities and the overall decision employs weighting factors directly related to the
doi:10.1007/s12559-009-9016-9
fatcat:gxmttfmq7rb4bdehpg5la5suni