CELP coding based on signal classification using the dyadic wavelet transform

This paper describes a CELP speech-coding algorithm which makes use of a specific signal classifier especially designed for this purpose. The classification method is based on the Dyadic Wavelet Transform (DyWT) and has proved to be superior to common classifiers that use the open-loop long-term prediction gain for mode selection. The classifier´s output is used for the control of several coder parameters, such as the choice of the subframe length and the selection of the synthesis model and the corresponding codebooks. We designed a fully quantised coder operating at a fixed bit rate of 4 kbit/s with a 20-ms frame. The proposed coder improves the weighted segmental signal-to-noise ratio (WSegSNR) by 2.3 dB on the average in comparison with a conventional CELP coder, thereby achieving high speech quality.