Noise-Robust Pitch Detection using Auto-correlation Function with Enhancements

An efficient noise-robust pitch detection algorithm is proposed in this paper. The algorithm is based on time domain autocorrelation function (ACF). A bank of band-pass filters is used for competitive contribution of periodicity to select primary pitch candidates. A weighting criterion that involves both increase and decrease in merit is applied to the candidates by exploiting the presence or the absence of pitch harmonics. Finally, a simple enhancement is integrated to smooth the pitch contour. The proposed algorithm is evaluated on TIMIT database in different types and levels of noise in terms of pitch and voice activity detection. The experimental results show the superiority of the proposed method over well known other methods.