Data Augmentation Using Multi-Input Multi-Output Source Separation for Deep Neural Network Based Acoustic Modeling

Yusuke Fujita, Ryoichi Takashima, Takeshi Homma, Masahito Togami. Data Augmentation Using Multi-Input Multi-Output Source Separation for Deep Neural Network Based Acoustic Modeling. In Nelson Morgan, editor, Interspeech 2016, 17th Annual Conference of the International Speech Communication Association, San Francisco, CA, USA, September 8-12, 2016. pages 3818-3822, ISCA, 2016. [doi]

@inproceedings{FujitaTHT16,
  title = {Data Augmentation Using Multi-Input Multi-Output Source Separation for Deep Neural Network Based Acoustic Modeling},
  author = {Yusuke Fujita and Ryoichi Takashima and Takeshi Homma and Masahito Togami},
  year = {2016},
  doi = {10.21437/Interspeech.2016-733},
  url = {http://dx.doi.org/10.21437/Interspeech.2016-733},
  researchr = {https://researchr.org/publication/FujitaTHT16},
  cites = {0},
  citedby = {0},
  pages = {3818-3822},
  booktitle = {Interspeech 2016, 17th Annual Conference of the International Speech Communication Association, San Francisco, CA, USA, September 8-12, 2016},
  editor = {Nelson Morgan},
  publisher = {ISCA},
}