Discriminatively trained recurrent neural networks for single-channel speech separation

@article{Weninger2014DiscriminativelyTR,
  title={Discriminatively trained recurrent neural networks for single-channel speech separation},
  author={Felix Weninger and John R. Hershey and Jonathan Le Roux and Bj{\"o}rn W. Schuller},
  journal={2014 IEEE Global Conference on Signal and Information Processing (GlobalSIP)},
  year={2014},
  pages={577-581}
}
This paper describes an in-depth investigation of training criteria, network architectures and feature representations for regression-based single-channel speech separation with deep neural networks (DNNs). We use a generic discriminative training criterion corresponding to optimal source reconstruction from time-frequency masks, and introduce its… CONTINUE READING

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