Emotional speech: towards a new generation of databases
Speech Communication - Special issue on speech and emotion
A study of cross-validation and bootstrap for accuracy estimation and model selection
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 2
IEEE Transactions on Audio, Speech, and Language Processing
Designing a hungarian multimodal database - speech recording and annotation
Proceedings of the Third COST 2102 international training school conference on Toward autonomous, adaptive, and context-aware multimodal interfaces: theoretical and practical issues
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Numerous difficulties, in the examination of emotions occurring in continuous spontaneous speech, are discussed in this paper, than different emotion recognition experiments are presented, using clauses as the recognition unit. In a testing experiment it was examined that what kind of acoustical features are the most important for the characterization of emotions, using spontaneous speech database. An SVM classifier was built for the classification of 4 most frequent emotions. It was found that fundamental frequency, energy, and its dynamics in a clause are the main characteristic parameters for the emotions, and the average spectral information, as MFCC and harmonicity are also very important. In a real life experiment automatic recognition system was prepared for a telecommunication call center. Summing up the results of these experiments, we can say, that clauses can be an optimal unit of the recognition of emotions in continuous speech.