NOISE-INVARIANT REPRESENTATION FOR SPEECH SIGNALS

A new group-delay based spectral domain is explored for representation of speech signals and for extraction of robust features. The spectrum is computed using the group-delay functions defined on the autocorrelation of a short segment of speech. The features derived from this spectrum are easy to compute and are robust to the background noise. The invariance of the spectral shape to noise in this domain is demonstrated by comparing the group-delay spectrum to the Discrete Fourier transform (DFT) based spectrum and the LPC-derived spectrum. The new domain representation can be applied for parameter estimation as well as speech recognition. In this paper we present preliminary results of using such features in Speaker-Dependent (SD) as well Speaker-Independent (SI) recognition systems.