Applications of Surface Correlation to the Estimation of the Harmonic Fundamental of Speech

Abstract

We present a method for estimating the fundamental frequency of harmonic signals, and apply this method to human speech. The method is based on cross-spectral methods, which provide accurate resolution of multicomponent FM signals in both time and frequency. The fundamental is re-introduced to the spectrum by a frequency-lag autocorrelation of the spectrum, even if the fundamental is completely missing in the original spectrum. By combining the different perspectives of the Fourier spectral representation and the time-lag autocorrelation function we suppress all components of harmonic signals except for the fundamental.