A time-frequency domain formant frequency estimation scheme for noisy speech signals

Abstract

Formant frequency is a one of the most important speech feature, which has widespread applications in speech recognition, synthesis, and compression. In this paper, a new time-frequency domain scheme for the estimation of formant frequencies from noise-corrupted speech signals is presented. In order to overcome the adverse effect of noise, instead of conventional autocorrelation function (ACF), a repeated ACF (RACF) of the noisy speech is employed. Exploiting the characteristics of the zero lag, a set of equations containing the lower lags of the RACF of the noisy speech is used to estimate the formant frequencies. In order to avoid estimation errors that may occur in the case of weak formants, a frequency-domain algorithm is introduced utilizing the RACF of the observed speech. Formant frequency estimation accuracy is measured for different natural and synthetic vowels in noisy environments and even at low levels of signal-to-noise ratio, a better performance is obtained by the proposed scheme in comparison to some of the existing methods.