Efficient encoding of mel-generalized cepstrum for CELP coders

The performance of several algorithms for the quantization of the mel-generalized cepstral coefficients is studied. First, the objective and subjective performance of two-stage vector quantization (VQ) is measured. It is shown that the subjective quality for the mel-generalized cepstral coefficients is higher than that for LSP. Secondly, interframe prediction is introduced in the encoding of mel-generalized cepstral coefficients. By utilizing interframe moving average (MA) prediction, the mel-generalized cepstral coefficients can be encoded more efficiently than LSP in terms of cepstral distortion. Finally, we implement a CELP coder based on mel-generalized cepstral analysis in which mel-generalized cepstral coefficients are quantized using MA prediction. This coder has a higher objective quality than conventional CELP