Title :
Efficient Speaker Recognition based on Multi-class Twin Support Vector Machines and GMMs
Author :
Cong, Hanhan ; Yang, Chengfu ; Pu, Xiaorong
Author_Institution :
Sch. of Comput. Sci. & Eng., Univ. of Electron. Sci. & Technol., Chengdu
Abstract :
This paper proposes a new approach for text-independent speaker recognition using twin support vector machines (TWSVMs) and feature extraction based on Gaussian mixture models (GMMs). Because of the perfect discriminability and the ability of managing large scale dataset, the proposed approach performs better than the traditional support vector machines (SVMs) on Ahumada Biometric Database and Gaudi Biometric Database.
Keywords :
Gaussian processes; speaker recognition; support vector machines; Ahumada Biometric Database; Gaudi Biometric Database; Gaussian mixture models; feature extraction; multi-class twin support vector machines; speaker recognition; Biometrics; Computational intelligence; Data mining; Feature extraction; Laboratories; Large-scale systems; Spatial databases; Speaker recognition; Support vector machine classification; Support vector machines;
Conference_Titel :
Robotics, Automation and Mechatronics, 2008 IEEE Conference on
Conference_Location :
Chengdu
Print_ISBN :
978-1-4244-1675-2
Electronic_ISBN :
978-1-4244-1676-9
DOI :
10.1109/RAMECH.2008.4681433
