Harmonicity based monaural speech dereverberation with time warping and F0 adaptive window

Although a number of dereverberation methods have been reported, dereverberation is still a challenging problem especially when a single microphone is used. To overcome this problem, we proposed a harmonicity based dereverberation method (HERB). HERB can blindly estimate the inverse filter of a room transfer function based on the harmonicity of speech signals and dereverberate the signals. However, HERB uses an imprecise assumption that hinders the dereverberation performance, that is, the fundamental frequency ( ) of a speech signal is assumed to be constant within a short time frame when extracting the features of harmonic components. In this paper, we combine HERB with time warping analysis and an adaptive window to remove this bottleneck. This extension makes it possible to estimate harmonic components precisely even when their frequencies change rapidly. Experiments show that time warping analysis with an adaptive window can effectively improve the dereverberation effect of HERB.