Abstract
A noise-robust, signal-to-noise ratio (SNR)-weighted correlogram-based pitch estimation algorithm (PEA) in which a bank of comb filters operates in each of the low, mid, and high frequency bands is proposed. Correlograms are obtained by applying autocorrelations directly on the low-freq filterbank (FBK) output, and the out put envelopes of all 3 FBKs. An SNR-weighting scheme is used for channel selection to yield a summary correlogram for each FBK. These summary correlograms are averaged to obtain an overall summary correlogram, which is time-smoothed before peak extraction is performed. The final pitch contour is obtained via dynamic programming. The proposed PEA is evaluated on the Keele corpus with additive white or babble noises. In comparison with widely-used PEAs, the proposed PEA has the lowest overall gross pitch error (GPE), especially in low SNR cases.
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