Noise Spectrum Estimation Using Line Spectral Frequencies for Robust Speech Recognition

Abstract

This paper presents a novel method for estimating reliable noise spectral magnitude for acoustic background noise suppression where only a single microphone recording is available. The proposed method finds noise estimates from spectral magnitudes measured at line spectral frequencies (LSFs), under the observation that adjacent LSFs are near the peak frequencies and isolated LSFs are close to the relatively flattened valleys of LPC spectra. The parameters used in the proposed method are LPC coefficients, their corresponding LSFs, and the gain of LPC residual signals, so it suits well to LPC-based speech coders.