Efficient encoding of mel-generalized cepstrum for CELP coders

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