Title :
Using vector quantization in Automatic Speaker Verification
Author :
Hayet, D. Jellai ; Tayeb, Laskri Mohamed
Author_Institution :
Dept. of Comput. Sci., Badji Mokhtar Univ., Annaba, Algeria
Abstract :
This article investigates several technique based on vector quantization (VQ) and maximum a posteriori adaptation (MAP) in Automatic Speaker Verification ASV. We propose to create multiple codebooks of Universal Background Model UBM by Vector Quantization and compare them with traditional approach in VQ, MAP adaptation and Gaussian Mixture Models.
Keywords :
maximum likelihood estimation; speaker recognition; ASV; Gaussian mixture models; MAP adaptation; UBM; VQ; automatic speaker verification; maximum a posteriori adaptation; multiple codebooks; universal background model; vector quantization; Adaptation models; Computational modeling; Speech; Training; Vector quantization; Vectors; Automatic Speaker Recognition; False Acceptance; False Rejection; Gaussian Mixture Models; Impostor Models; Linde Buzo Gray Algorithm; Speaker Verification; Vector Quantization;
Conference_Titel :
Information Technology and e-Services (ICITeS), 2012 International Conference on
Conference_Location :
Sousse
Print_ISBN :
978-1-4673-1167-0
DOI :
10.1109/ICITeS.2012.6216611
