DocumentCode
673324
Title
Automatic speaker recognition using a unique personal feature vector and Gaussian Mixture Models
Author
Kaminski, Kamil ; Majda, Ewelina ; Dobrowolski, Andrzej P.
Author_Institution
Fac. of Electron., Mil. Univ. of Technol., Warsaw, Poland
fYear
2013
fDate
26-28 Sept. 2013
Firstpage
220
Lastpage
225
Abstract
This article presents an automatic speaker recognition system implemented in Matlab, which uses a unique feature vector, the so-called “Voice Print” (VP), to describe the voice. The system uses Gaussian Mixtures Models (GMM) in the classification process. The final part of the paper presents research on the efficiency of speaker recognition for different variants of the system, as well as the results of optimisation of the system.
Keywords
Gaussian processes; feature extraction; speaker recognition; speech processing; GMM; Gaussian mixture model; Matlab; automatic speaker recognition system; feature extraction; unique personal feature vector; voice print; Analytical models; Computer architecture; Industries; MATLAB; Mathematical model; Training; Vectors; ASR systems; GMM; Gaussian Mixtures Models; feature extraction; speaker recognition; speech signal;
fLanguage
English
Publisher
ieee
Conference_Titel
Signal Processing: Algorithms, Architectures, Arrangements, and Applications (SPA), 2013
Conference_Location
Poznan
ISSN
2326-0262
Electronic_ISBN
2326-0262
Type
conf
Filename
6710629
Link To Document