Speaker recognition employing waveform based signal representation in nonorthogonal multiple transform domains

Automatic speaker recognition (ASR) technique employing split vector quantized speech representation in multiple transform domains is presented. In this approach, a set of appropriate transform domains are selected and a vector quantized codebook is generated in each of these selected transform domains for the signal waveform. For each speaker, each signal vector is represented from the codebooks that yield the highest accuracy of representation. The algorithm is given and a performance measure is developed and used to evaluate the algorithm performance. Improved speech recognition accuracy was consistently obtained employing the proposed technique in comparison with vector quantization employing single transform VQ representations. Sample results for 10 speakers are presented to illustrate the considerable performance improvement for ASR