Paper Info
Title
Noise-robust F0 estimation using SNR-weighted summary correlograms from multi-band comb filters
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.
Year
DOI
Venue
2011
10.1109/ICASSP.2011.5947345
ICASSP
Keywords
Field
DocType
speech processing,pea,comb filtering,snr-weighted summary correlogram,multi-band,low-freq filterbank,pitch estimation algorithm,noise-robust f0 estimation,pitch estimation,gpe,gross pitch error,fbk,noise-robustness,multiband comb filter,correlogram,comb filters,keele corpus,signal-to-noise ratio,signal to noise ratio,estimation,noise measurement,speech,correlation,high frequency,harmonic analysis
Pitch contour,Speech processing,Comb filter,Pattern recognition,Noise measurement,Computer science,Signal-to-noise ratio,Filter bank,Artificial intelligence,Correlogram,Radio spectrum
Conference
ISSN
ISBN
Citations 
1520-6149 E-ISBN : 978-1-4577-0537-3
978-1-4577-0537-3
8
PageRank 
References 
Authors
0.92
8
2
Name
Order
Citations
PageRank
Lee Ngee Tan1435.00
Abeer Alwan272988.19