Multimodal code-excited linear prediction (CELP) coder and method using peakiness measure

摘要

A multimodal code-excited linear prediction (CELP) speech coder determines a pitch-lag-periodicity-independent peakiness measure from the input speech. If the measure is greater than a peakiness threshold the encoder classifies the speech in a first coding mode. In one embodiment only frames having an open-loop pitch prediction gain not greater than a threshold, a zero-crossing rate not less than a threshold, and a peakiness measure not greater than the peakiness threshold will be classified as unvoiced speech. Accordingly, the beginning or end of a voiced utterance will be properly coded as voiced speech and speech quality improved. In another embodiment, gain-match scaling matches coded speech energy to input speech energy. A target vector (the portion of input speech with any effects of previous signals removed) is approximated using the precomputed gain for excitation vectors while minimizing perceptually-weighted error. The correct gain value is perceptually more important than the shape of the excitation vector for most unvoiced signals.