Improving Music Source Separation Based on Deep Neural Networks through Data Augmentation and Network Blending

Venue

2017 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp. 261-265

Publication Year

2017

Keywords

speech processing,Instruments,music,Source separation,Training,Blending,blending scheme yields,Context,data augmentation,Deep neural network (DNN),deep neural network architectures,Indexes,Long-short term memory (LSTM),mixture models,multichannel Wiener filter post-processing,Music source separation (MSS),music source separation improvement,recurrent network,recurrent neural nets,Recurrent neural networks,SiSEC DSD100 dataset,Wiener filters

Identifiers

Authors

  • S. Uhlich
  • M. Porcu
  • F. Giron
  • M. Enenkl
  • T. Kemp
  • N. Takahashi
  • Y. Mitsufuji

Source Materials