Guided spectrogram filtering for speech dereverberation

Abstract Guided filtering is a computationally efficient and powerful technique used in image processing applications, such as edge-preserving smoothing, details enhancing and single image dehazing. In this paper, we propose a novel single channel speech dereverberation method using guided spectrogram filtering by considering a speech spectrogram as an image. The proposed method requires neither room acoustic parameter estimation nor late reverberant spectral variance estimation. Objective test results show the validity of the guided spectrogram filtering method for speech dereverberation. Compared with state-of-the-art speech dereverberation methods, the proposed method has better performance in terms of perceptual evaluation of speech quality (PESQ), speech-to-reverberation modulation energy ratio (SRMR) and short-time objective intelligibility (STOI) in most cases.

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