In this paper, we propose a novel residual echo suppression (RES) algorithm constructed in the acoustic echo canceller. In the proposed approach, we introduce a statistical model to detect the signal components of the output signal and the state of signal is classified into four distinct hypothesis depending on the activity of near-end signal and residual echo. For hypothesis testing, the conventional likelihood ratio test is performed to make an optimal decision. The parameters specified in terms of the power spectral densities can be obtained by updating according to the hypothesis testing results and we can obtain the optimal RES filter by adopting the estimated parameters. The experimental results show that the proposed algorithm yields improved performance compared to that of the previous RES technique.
Bibliographic reference. Lee, Seung Yeol / Shin, Jong Won / Yun, Hwan Sik / Kim, Nam Soo (2007): "A statistical model based post-filtering algorithm for residual echo suppression", In INTERSPEECH-2007, 858-861.