Speech compression with preservation of speaker identity

Although much effort has been directed recently towards speech compression at rates below 4 kb/s, the primary metric for comparison has, understandably, been the amount of spectral distortion in the decompressed speech. However, an aspect which is becoming important in some applications is the ability to identify the original speaker from the coded speech algorithmically. We investigate here the effect of speech compression using multistage vector quantization of the short-term (formant) filter parameters on text-independent speaker identification. It is demonstrated that in cases where the speech is stored in a compressed database for retrieval, the speaker model should be constructed from the raw speech before spectral compression. Additionally, Gaussian models of sufficiently high order are able to reduce the negative effects of spectral vector quantization upon speaker identification accuracy.