Learning spectral mapping for speech dereverberation

@article{Han2014LearningSM,
  title={Learning spectral mapping for speech dereverberation},
  author={Kun Han and Yuxuan Wang and DeLiang Wang},
  journal={2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)},
  year={2014},
  pages={4628-4632}
}
Reverberation distorts human speech and usually has negative effects on speech intelligibility, especially for hearing-impaired listeners. It also causes performance degradation in automatic speech recognition and speaker identification systems. Therefore, the dereverberation problem must be dealt with in daily listening environments. We propose to use deep neural networks (DNNs) to learn a spectral mapping from the reverberant speech to the anechoic speech. The trained DNN produces the… CONTINUE READING
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