A method for pitch extraction of speech signals using autocorrelation functions through multiple window lengths

摘要

A high-performance method for pitch extraction is proposed for the purposes of real-time sequential speech processing that can be used in such applications as speech rate conversion systems. according to this method, auto- correlation functions of the input speech waveforms are calculated for one analyzed point in time using multiple lengths of the analysis windows, and the largest peaks of each autocorrelation function are detected within the appro- priate ranges, after which the optimum pitch period is selected by weighting the candidates of the pitch period obtained by the number of windows.