On Discriminative Framework for Single Channel Audio Source Separation

@inproceedings{Gang2016OnDF,
  title={On Discriminative Framework for Single Channel Audio Source Separation},
  author={Arpita Gang and Pravesh Biyani},
  booktitle={INTERSPEECH},
  year={2016}
}
Sound sources are a very common everyday occurrence. But a single audio source is seldom heard alone. There is a sea of applications, like speech recognition, where an isolated sound source is desirable. This makes audio source separation a very important problem. In this thesis, we focus on the single channel source separation (SCSS) problem, which implies separation of individual sources from a single observation. The problem of finding many unknowns from one equation makes this problem ill… CONTINUE READING

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Supervised monaural source separation based on autoencoders

  • 2017 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
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