Adaptive filtering for music/voice separation exploiting the repeating musical structure

Antoine Liutkus*, Zafar Rafii, Roland Badeau, Bryan A Pardo, Gael Richard

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

51 Scopus citations

Abstract

The separation of the lead vocals from the background accompaniment in audio recordings is a challenging task. Recently, an efficient method called REPET (REpeating Pattern Extraction Technique) has been proposed to extract the repeating background from the non-repeating foreground. While effective on individual sections of a song, REPET does not allow for variations in the background (e.g. verse vs. chorus), and is thus limited to short excerpts only. We overcome this limitation and generalize REPET to permit the processing of complete musical tracks. The proposed algorithm tracks the period of the repeating structure and computes local estimates of the background pattern. Separation is performed by soft time-frequency masking, based on the deviation between the current observation and the estimated background pattern. Evaluation on a dataset of 14 complete tracks shows that this method can perform at least as well as a recent competitive music/voice separation method, while being computationally efficient.

Original languageEnglish (US)
Title of host publication2012 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2012 - Proceedings
Pages53-56
Number of pages4
DOIs
StatePublished - 2012
Event2012 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2012 - Kyoto, Japan
Duration: Mar 25 2012Mar 30 2012

Publication series

NameICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
ISSN (Print)1520-6149

Other

Other2012 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2012
CountryJapan
CityKyoto
Period3/25/123/30/12

Keywords

  • Music/voice separation
  • adaptive algorithms
  • repeating pattern
  • time-frequency masking

ASJC Scopus subject areas

  • Software
  • Signal Processing
  • Electrical and Electronic Engineering

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    Liutkus, A., Rafii, Z., Badeau, R., Pardo, B. A., & Richard, G. (2012). Adaptive filtering for music/voice separation exploiting the repeating musical structure. In 2012 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2012 - Proceedings (pp. 53-56). [6287815] (ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings). https://doi.org/10.1109/ICASSP.2012.6287815