One Microphone Blind Dereverberation Based on Quasi-periodicity of Speech Signals

Nakatani, Tomohiro, Miyoshi, Masato, Kinoshita, Keisuke

Neural Information Processing Systems 

Speech dereverberation is desirable with a view to achieving, for example, robust speech recognition in the real world. However, it is still a challenging problem, especially when using a single microphone. Although blind equalization techniques have been exploited, they cannot deal with speech signals appropriately because their assumptions are not satisfied by speech signals. We propose a new dereverberation principle based on an inherent property of speech signals, namely quasi-periodicity. The present methods learn the dereverberation filter from a lot of speech data with no prior knowledge of the data, and can achieve high quality speech dereverberation especially when the reverberation time is long.

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