A two-step speech compression system with vector quantizing

A training sequence of speech data is used to design a two-step speech compression system, based upon either single speakers or multiple speakers. The system is designed to minimize an average spectral distortion over the training sequence, leading to an identification step using linear prediction techniques followed by a vector quantizer. The system is then used to compress test sequences of speech data, leading to much lower bit rates than obtained using scalar quantization for equivalent distortions. For the same numerical distortion, 20-bits/frame were required using optimal scalar bit allocation and quantization, whereas 8-bits/frame were required using vector quantization. Results are presented in the form of numerical distortion measures and analog tapes of synthesized speech.