Title :
A connectionist approach for automatic speaker identification
Author :
Bennani, Younés ; Soulie, Françoise Fogelman ; Gallinari, Patrick
Author_Institution :
Lab. de Recherche en Inf., Univ. de Paris Sud, Orsay, France
Abstract :
A connectionist approach to automatic speaker identification based on the learning vector quantization (VQ) algorithm is presented. For each adherent to the identification system, a number of references is fixed. The algorithm is based on a nearest-neighbor principle, with adaptation through learning. The identification is realized by comparing to a given threshold the distance of the unknown utterance to the nearest reference. Preliminary tests run on a ten-speaker set show an identification rate of 97% for MFC coefficients. The identification system and database used and the results obtained for different combinations of parameters are given. The system is evaluated by comparing its performances with a Bayesian system
Keywords :
learning systems; speech recognition; Bayesian system; MFC coefficients; automatic speaker identification; connectionist approach; identification rate; learning vector quantization; nearest-neighbor principle; unknown utterance; Bayesian methods; Buildings; Databases; Linear predictive coding; Mel frequency cepstral coefficient; Microphones; Nearest neighbor searches; Performance evaluation; Speech; System testing; Testing; Vector quantization;
Conference_Titel :
Acoustics, Speech, and Signal Processing, 1990. ICASSP-90., 1990 International Conference on
Conference_Location :
Albuquerque, NM
DOI :
10.1109/ICASSP.1990.115619
