Online Speech Dereverberation Using
Kalman Filter and EM Algorithm
Abstract— Online Speech Dereverberation Using Kalman Filter and EM Algorithm. Speech signals recorded in a room are commonly degraded by reverberation. In most cases, both the speech sign a land the acoustic system of the room are unknown and time-varying. In this paper, a scenario with a single desired sound source and lowly time-varying and spatially white noise is considered, and a multi-microphone algorithm that simultaneously estimates the clean speech signal and the time-varying acoustic system is proposed. The recursive ex pectation-maximization scheme is employed to obtain both the clean speech signal and the acoustic system in an online manner. In the expectation step, the Kalman ﬁlter is applied to extract a new sample of the clean signal, and in the maximization step, the system estimate is updated according to the output of the Kalman ﬁlter. Experimental results show that the proposed method is able to < Final Yeat Projcts 2016 > signiﬁcantly reduce reverberation and increase the speech quality. Moreover, the tracking ability of the algorithm was validated in practical scenarios using human speakers moving in a natural manner.
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