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.