This Letter proposes an optimal gain filter for the perceptual acoustic echo suppressor. We designed an optimally-modified log-spectral amplitude estimation algorithm for the gain filter in order to achieve robust suppression of echo and noise. A new parameter including information about interferences (echo and noise) of single-talk duration is statistically analyzed, and then the speech absence probability and the a posteriori SNR are judiciously estimated to determine the optimal solution. The experiments show that the proposed gain filter attains a significantly improved reduction of echo and noise with less speech distortion.

This paper proposes a new echo suppressor based on spectral correlation between the residual echo and the echo replica in an ordinary echo canceller. First, it is revealed by experiments that there is a significant correlation between the spectral amplitudes of the residual echo and the echo replica, and a new model for nonlinear-echo suppression based on the correlation is derived. Next, a new echo suppressor controlling the gain in each frequency bin to suppress the residual echo based on the new model is developed. Simulation results with speech data recorded by a hands-free cellphone show that the proposed echo suppressor reduces the residual echo to an almost inaudible level.