One Microphone Blind Dereverberation Based on Quasi-Periodicity of Speech Signals
Abstract
Speech dereverberation is desirable with a view to achieving, for exam- ple, robust speech recognition in the real world. However, it is still a chal- lenging 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.
Cite
Text
Nakatani et al. "One Microphone Blind Dereverberation Based on Quasi-Periodicity of Speech Signals." Neural Information Processing Systems, 2003.Markdown
[Nakatani et al. "One Microphone Blind Dereverberation Based on Quasi-Periodicity of Speech Signals." Neural Information Processing Systems, 2003.](https://mlanthology.org/neurips/2003/nakatani2003neurips-one/)BibTeX
@inproceedings{nakatani2003neurips-one,
title = {{One Microphone Blind Dereverberation Based on Quasi-Periodicity of Speech Signals}},
author = {Nakatani, Tomohiro and Miyoshi, Masato and Kinoshita, Keisuke},
booktitle = {Neural Information Processing Systems},
year = {2003},
pages = {1417-1424},
url = {https://mlanthology.org/neurips/2003/nakatani2003neurips-one/}
}