Pitch extraction algorithm for voice recognition applications

Abstract

Two computationally simple pitch-extraction algorithms based on the autocorrelation method of pitch determination are presented. Both algorithms have been implemented in software, and their performance has been evaluated. The first pitch-extraction algorithm (PEA Hash 1) uses center clipping and infinite peak dipping for time-domain preprocessing before computing autocorrelation while the second algorithm (PEA Hash 2) nonlinearly distorts the speech signal before center clipping and autocorrelation computation. PEA Hash 2 provides a better pitch detection estimate than PEA Hash 1 and also eliminates the need to adjust critically the clipping level threshold. The initial results obtained by comparing the average gross pitch error rate suggest that PEA Hash 2 is better (by a factor of two or more) than PEA Hash 1.<>