Use of the pitch synchronous wavelet transform as a new decomposition method for WI

A new characteristic waveform decomposition method based on wavelets is proposed for the waveform interpolation (WI) paradigm. In WI, pitch-cycle waveforms are filtered in the evolution domain to decompose the signal into two waveform surfaces, one characterising voiced speech and a second representing unvoiced speech. The slow roll-off of FIR filters leads, however, to a significant inter-relationship between the decomposed surfaces. We present the pitch synchronous wavelet transform (PSWT) as an alternative decomposition mechanism. Filtering is again performed in the evolutionary waveform domain, producing characteristic surfaces at several resolutions. This multi-scale characterisation leads to more flexible quantisation of parameters, especially at higher rates than WI´s 2.4 kb/s. FIR filters are replaced in the wavelet filter bank by causal, stable FIR filters which achieve significant delay reductions over their IIR counterparts. Furthermore, FIR filters track the dynamic aspects of the evolutionary surfaces faster, overcoming problems existing in the current WI decomposition