A Deep Ensemble Learning Method for Monaural Speech Separation

@article{Zhang2016ADE,
  title={A Deep Ensemble Learning Method for Monaural Speech Separation},
  author={Xiao-Lei Zhang and DeLiang Wang},
  journal={IEEE/ACM Transactions on Audio, Speech, and Language Processing},
  year={2016},
  volume={24},
  pages={967-977}
}
Monaural speech separation is a fundamental problem in robust speech processing. Recently, deep neural network (DNN)-based speech separation methods, which predict either clean speech or an ideal time-frequency mask, have demonstrated remarkable performance improvement. However, a single DNN with a given window length does not leverage contextual information sufficiently, and the differences between the two optimization objectives are not well understood. In this paper, we propose a deep… CONTINUE READING
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