A spectral/temporal method for robust fundamental frequency tracking

Abstract

In this paper, a fundamental frequency (F(0)) tracking algorithm is presented that is extremely robust for both high quality and telephone speech, at signal to noise ratios ranging from clean speech to very noisy speech. The algorithm is named "YAAPT," for "yet another algorithm for pitch tracking." The algorithm is based on a combination of time domain processing, using the normalized cross correlation, and frequency domain processing. Major steps include processing of the original acoustic signal and a nonlinearly processed version of the signal, the use of a new method for computing a modified autocorrelation function that incorporates information from multiple spectral harmonic peaks, peak picking to select multiple F(0) candidates and associated figures of merit, and extensive use of dynamic programming to find the "best" track among the multiple F(0) candidates. The algorithm was evaluated by using three databases and compared to three other published F(0) tracking algorithms by using both high quality and telephone speech for various noise conditions. For clean speech, the error rates obtained are comparable to those obtained with the best results reported for any other algorithm; for noisy telephone speech, the error rates obtained are lower than those obtained with other methods.