Semi-blind algorithm for joint noise suppression and dereverberation based on higher-order statistics and acoustic model likelihood.

In this paper, we propose an automatic optimization scheme of FD-BSE-based joint suppression of noise and late reverberation to improve the speech recognition accuracy for spoken-dialogue system. First, we optimize the parameter of conventional FD-BSE-based method using the assessment of musical noise measured by higher-order statistics and acoustic model likelihood. Next, to maintain the optimum performance of the system, we proposed the switching scheme using the distance information provided by image sensor. The experimental results show that the proposed approach improves the word recognition accuracy.