Title :
A comparison between hidden Markov models and vector quantization for speech independent speaker recognition
Author :
Weber, D.M. ; Du Preez, J.X.
Author_Institution :
Dept. of Electr. & Electron. Eng., Stellenbosch Univ., South Africa
Abstract :
We compare Vector Quantization and Hidden Markov Models for speaker recognition for real time recognition. A scheme to reject speakers not known to the system is described and tested. Results show that the HMM algorithm outperforms the VQ algorithm. Using a 64 state HMM, a speaker recognition accuracy of 96.1% was achieved. The rejection option generated 25.7% false rejections for a 95% confidence of a correct decision. VQ best results were 93.1% with a 61% false rejection rate for codebooks of size 128
Keywords :
hidden Markov models; speaker recognition; speech coding; vector quantisation; HMM algorithm; VQ algorithm; codebooks; false rejections; hidden Markov models; real time recognition; speaker recognition accuracy; speech independent speaker recognition; vector quantization; Africa; Electronic equipment testing; Feature extraction; Hidden Markov models; Loudspeakers; Real time systems; Speaker recognition; Speech processing; System testing; Vector quantization;
Conference_Titel :
Communications and Signal Processing, 1993., Proceedings of the 1993 IEEE South African Symposium on
Conference_Location :
Jan Smuts Airport
Print_ISBN :
0-7803-1292-9
DOI :
10.1109/COMSIG.1993.365856
