Fundamentals of speech recognition
Fundamentals of speech recognition
Recognizing emotions for the audio-visual document indexing
ISCC '04 Proceedings of the Ninth International Symposium on Computers and Communications 2004 Volume 2 (ISCC"04) - Volume 02
Comparison of Classification Methods for Detecting Emotion from Mandarin Speech
IEICE - Transactions on Information and Systems
Emotion recognition from speech: a review
International Journal of Speech Technology
Emotion recognition from speech using source, system, and prosodic features
International Journal of Speech Technology
Comparison of complementary spectral features of emotional speech for german, czech, and slovak
COST'11 Proceedings of the 2011 international conference on Cognitive Behavioural Systems
Dimensionality reduction-based spoken emotion recognition
Multimedia Tools and Applications
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Combining different feature streams to obtain a more accurate experimental result is a well-known technique. The basic argument is that if the recognition errors of systems using the individual streams occur at different points, there is at least a chance that a combined system will be able to correct some of these errors by reference to the other streams. In the emotional speech recognition system, there are many ways in which this general principle can be applied. In this paper, we proposed using feature selection and feature combination to improve the speaker-dependent emotion recognition in Mandarin speech. Five basic emotions are investigated including anger, boredom, happiness, neutral and sadness. Combining multiple feature streams is clearly highly beneficial in our system. The best accuracy recognizing five different emotions can be achieved 99.44% by using MFCC, LPCC, RastaPLP, LFPC feature streams and the nearest class mean classifier.