Ambiguity reduction in speaker identification by the relaxation labeling process

A nonlinear probabilistic model of the relaxation labeling (RL) process is implemented in the speaker identification task in order to disambiguate the labeling of the speech feature vectors. In this proposed algorithm, the de terministic labeling of the vector quantization (VQ)-based speaker identifi cation is relaxed by means of introducing initial probabilistic weights to the labeling process of the speech feature vectors. This process is then it eratively updated until no further significant improvement is found. Experi mental results on speaker identification using a commercial speech corpus s how that the relaxation labeling outperforms the conventional VQ method. (C ) 1999 Pattern Recognition Society. Published by Elsevier Science Ltd. All rights reserved.