An improved two-stage dereverberation method based on bayesian estimation of a speech source

It is not easy to extract speech emanating from a specific direction in a large reverberant room with additional sound sources. Many of the existing methods work well only if there is a single sound source, and their performance degrades if additional sound sources are present. In this work, we have addressed this problem by maximizing the posterior probability of speech signal as computed by use of Bayes' Theorem. Our de-reverb method is two-staged. We have evaluated the efficacy of our method against several popular methods in terms of five objective measures; Signal-to-Interference Ratio, Log-Likelihood Ratio, Cepstrum Distance, Frequency-Weighted Segment SNR, and Speechto-Reverberation Modulation Energy Ratio. We show that on each of these parameters, the method proposed in this work performs better than the one we have benchmarked it against.