Title :
Support vector machines approaches and its application to speaker identification
Author :
Boujelbene, S. Zribi ; Mezghani, D. Ben Ayed ; Ellouze, N.
Author_Institution :
Inf. Dept., FSHST, Tunisia
Abstract :
This paper proposes a classification approach that incorporates the statistical methods GMM and support vector machines. The proposed GMM-SVM system is presented and experimentally evaluated on text independent speaker identification. Our results prove that the combination approach GMM-SVM is significantly superior than SVM approach. We report improvements of 85,37% amelioration in identification rate compared to the SVM identification rate.
Keywords :
Gaussian processes; speaker recognition; statistical analysis; support vector machines; GMM-SVM system; gaussian mixture model; statistical method; support vector machine approach; text independent speaker identification; Ecosystems; Electronic mail; Gaussian processes; Informatics; Intersymbol interference; Power system modeling; Speaker recognition; Speech; Support vector machine classification; Support vector machines; Gaussian mixture models; speaker identification; support vector machines;
Conference_Titel :
Digital Ecosystems and Technologies, 2009. DEST '09. 3rd IEEE International Conference on
Conference_Location :
Istanbul
Print_ISBN :
978-1-4244-2345-3
Electronic_ISBN :
978-1-4244-2346-0
DOI :
10.1109/DEST.2009.5276751
