Band-adaptive formant frequency estimation from noisy speech in correlation domain

Shaikh Anowarul Fattah, Wei-Ping Zhu, M. Omair Ahmad


A study was conducted to estimate formant frequencies accurately under a severe noisy condition. A band-limited repeated autocorrelation function (RACF) was introduced of the observed noisy speech to overcome the adverse impact of noise. It was shown that the RACF was pole-preserving and capable of reducing the effect of noise significantly. A band-adaptive filter-bank was employed on a zero lag compensated ACF to separate each formant frequency region before the formant estimation. Autocorrelation operation was repeated on each of the resulting band-limited ACFs and a spectral peak picking method was employed to each of the band-limited RACFs to extract formant frequencies. The proposed algorithm was tested on synthetic and natural speech signals in the presence of noise.


Adaptive filters; Algorithms; Correlation detectors; Electric filters; Natural frequencies; Regression analysis; Autocorrelation functions; Correlation domains; Formant estimation; Formant frequency; Formant frequency estimation; Impact of noise; Natural speech; Noisy speech; Spectral peak

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