DocumentCode :
698863
Title :
Passive versus active: Vocal classification system
Author :
Hammal, Z. ; Bozkurt, B. ; Couvreur, L. ; Unay, D. ; Caplier, A. ; Dutoit, T.
Author_Institution :
Lab. of images & signals LIS, Grenoble, France
fYear :
2005
fDate :
4-8 Sept. 2005
Firstpage :
1
Lastpage :
4
Abstract :
Five expressions are commonly considered to characterize human emotional states: Happiness, Surprise, Anger, Sadness and Neutral. Different measures can be extracted from speech signals to characterize these expressions, for example the pitch, the energy, the SPI and the speech rate. Automatic classification of the five expressions based on these features shows a great confusion between Anger, Surprise and Happiness on the one hand and Neutral and Sadness on the other hand. Such a confusion is also observed when humans make the same classification. We propose to define two classes of expression: Active gathering Happiness, Surprise and Anger versus Passive gathering Neutral and Sadness. Such a partition is also better suited for the integration of speech information in a multimodal classification system based on speech and video, which is the long term aim of our work. In this paper, we test several classification methods, namely a Bayesian classifier, a Linear Discriminant Analysis (LDA), the K Nearest Neighbours (KNN) and a Support Vector Machine with gaussian radial basis function kernel (SVM). For the considered two classes, the best performances are achieved with the SVM classifier with a recognition rate of 89.74% for Active state and of 86.54 % for Passive state.
Keywords :
Bayes methods; image classification; radial basis function networks; speech recognition; support vector machines; Bayesian classifier; K nearest neighbours; KNN; LDA; SPI; SVM classifier; anger; automatic classification; gaussian radial basis function kernel; happiness; human emotional states; linear discriminant analysis; multimodal classification system; neutral; passive gathering state versus active gathering state; pitch; recognition rate; sadness; speech information integration; speech rate; speech signal extraction; support vector machine; surprise; video; vocal classification system; Acoustics; Bayes methods; Databases; Feature extraction; Speech; Standards; Support vector machines;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Signal Processing Conference, 2005 13th European
Conference_Location :
Antalya
Print_ISBN :
978-160-4238-21-1
Type :
conf
Filename :
7078460
Link To Document :
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