Title :
Determining Efficiency of Speech Feature Groups in Emotion Detection
Author :
Polat, G. ; Altun, Hallis
Author_Institution :
Nigde Univ. Yuksek Lisans Ogrencisi, Nigde
Abstract :
Features, extract from speech parameter are frequently used in emotion detection problem. Prosodic, MFCC, LPC and band energy feature groups are commonly used in literature to detect emotion in speech. The aim of the study is to examine the efficiency of these features groups in emotion detection problem using a SVM classifier.
Keywords :
emotion recognition; feature extraction; speech recognition; support vector machines; SVM classifier; emotion detection; speech feature groups; speech parameter; Feature extraction; Linear predictive coding; Mel frequency cepstral coefficient; Speech; Support vector machine classification; Support vector machines;
Conference_Titel :
Signal Processing and Communications Applications, 2007. SIU 2007. IEEE 15th
Conference_Location :
Eskisehir
Print_ISBN :
1-4244-0719-2
Electronic_ISBN :
1-4244-0720-6
DOI :
10.1109/SIU.2007.4298582
