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NOISE-ROBUST F0 ESTIMATION USING SNR-WEIGHTED SUMMARY CORRELOGRAMS FROM MULTI-BAND COMB FILTERS
 

Summary: NOISE-ROBUST F0 ESTIMATION USING SNR-WEIGHTED SUMMARY CORRELOGRAMS
FROM MULTI-BAND COMB FILTERS
Lee Ngee Tan and Abeer Alwan
Department of Electrical Engineering, University of California, Los Angeles
{tleengee, alwan}@ee.ucla.edu
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 autocorrela-
tions 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 sum-
mary correlogram, which is time-smoothed before peak extraction
is performed. The final pitch contour is obtained via dynamic pro-
gramming. 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.

  

Source: Alwan, Abeer - Electrical Engineering Department, University of California at Los Angeles

 

Collections: Computer Technologies and Information Sciences