Active speech level estimation in noisy signals with quadrature noise suppression

Abstract

We present a noise-robust algorithm for estimating the active level of speech, which is the average speech power during intervals of speech activity. The proposed algorithm uses the clean speech phase to remove the quadrature noise component from the short-time power spectrum of the noisy speech, as well as SNR-dependent techniques to improve the estimation. The pitch of voiced speech frames is determined using a noise-robust pitch tracker and the speech level is estimated from the energy of the pitch harmonics using the harmonic summation principle. At low noise levels, the resultant active speech level estimate is combined with that from the standardized ITU-T P.56 algorithm to give a final composite estimate. The algorithm has been evaluated using a range of noise signals and gives consistently lower errors than previous methods and than the ITU-T P.56 algorithm, which is accurate for SNR levels of above 15 dB.