Singing-voice separation from monaural recordings using robust principal component analysis

@article{Huang2012SingingvoiceSF,
  title={Singing-voice separation from monaural recordings using robust principal component analysis},
  author={Po-Sen Huang and Scott Deeann Chen and Paris Smaragdis and Mark Hasegawa-Johnson},
  journal={2012 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)},
  year={2012},
  pages={57-60}
}
  • Po-Sen Huang, Scott Deeann Chen, +1 author Mark Hasegawa-Johnson
  • Published in
    IEEE International Conference…
    2012
  • Computer Science
  • Separating singing voices from music accompaniment is an important task in many applications, such as music information retrieval, lyric recognition and alignment. Music accompaniment can be assumed to be in a low-rank subspace, because of its repetition structure; on the other hand, singing voices can be regarded as relatively sparse within songs. In this paper, based on this assumption, we propose using robust principal component analysis for singing-voice separation from music accompaniment… CONTINUE READING

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