Quantization of non-linear predictors in speech coding

Abstract

Discusses how to exploit the nonlinearities in speech with the main purpose of improving the prediction in speech coders. If non-linearities are absent from speech the linear technique is sufficient, but if non-linearities are present the technique is inadequate and more sophisticated predictors are called for. Thyssen et al. (1994) gave evidence for non-linearities in speech and presented two non-linear short-term predictors that both were superior to the linear predictor without quantization. The present authors give methods to design vector quantizers for the non-linear predictors and investigate how vector quantization of the non-linear predictors affects prediction. Furthermore, they compare the performance of the quantized non-linear predictors to the performance of traditional quantized linear predictors. The experiments show that 10-bit VQ of the non-linear predictor leads to similar performance as 20-bit state-of-the-art split VQ of the LSP-parameters.