Signal/noise KLT based approach for enhancing speech degraded by colored noise

Abstract

A signal/noise Karhunen-Loeve transform (KLT) based approach for enhancing speech degraded by colored noise is proposed. The noisy speech frames are classified into speech-dominated frames and noise-dominated frames. In the speech-dominated frames, the signal KLT matrix is used and in the noise dominated frames, the noise KLT matrix is used. The approach does not require noise whitening and hence works well even with narrowband noise. A two-dimensional objective measure which captures both the speech distortion and the noise shaping characteristics of the algorithm is proposed. This measure indicates that the proposed method performs better noise shaping than a modified form of the signal subspace approach proposed by Ephraim and Van Trees (1995) and the standard spectral subtraction method. Informal listening tests show that the proposed algorithm does not suffer from the problem of residual musical noise and performs better noise masking than the signal subspace approach.