Multi-Target Ensemble Learning for Monaural Speech Separation

@inproceedings{Zhang2017MultiTargetEL,
  title={Multi-Target Ensemble Learning for Monaural Speech Separation},
  author={Hui Bin Zhang and Xueliang Zhang and Guanglai Gao},
  booktitle={INTERSPEECH},
  year={2017}
}
Speech separation can be formulated as a supervised learning problem where a machine is trained to cast the acoustic features of the noisy speech to a time-frequency mask, or the spectrum of the clean speech. These two categories of speech separation methods can be generally referred as the masking-based and the mapping-based methods, but none of them can perfectly estimate the clean speech, since any target can only describe a part of the characteristics of the speech. However, the estimated… Expand
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