A robust algorithm for formant frequency extraction of noisy speech

In this paper a new method for formant frequency estimation of noisy speech is proposed based on linear prediction analysis. Usually the linear prediction analysis based algorithms can extract the formant frequencies effectively for clean speech. When speech is corrupted by noise, however, their performance degrades seriously. It is well known that the autocorrelation function has the property of concentrating the energy of the white noise in the vicinity of the zero lag. Utilizing this property of the autocorrelation function, the proposed method extracts the formant frequencies from the autocorrelation function of the speech instead of the speech itself. The experimental results show that the proposed method is much more robust to noise than the conventional linear prediction based algorithms