Temporal decomposition: a promising approach to VQ-based speaker identification

In this paper, a new set of features is proposed that has been found to improve the performance of automatic speaker identification systems. The new set of features is referred to as "even targets". The new features have been derived from line spectral frequency (LSF) parameters using the so-called "temporal decomposition" (TD) technique. The number of feature vectors required for both training and testing phases has been reduced by one-fifth compared to that of the traditional mel-frequency cepstrum coefficients (MFCC) features, while the identification results obtained are comparable or even better. Also, this work introduces one more application of TD (speaker recognition) in addition to speech coding, speech segmentation, and speech recognition. It shows that the event targets in TD can convey information about the identity of a speaker.