Vocal separation using improved robust principal component analysis and post-processing

Tomohiro Watanabe, Takanori Fujisawa, Masaaki Ikehara

研究成果: Conference contribution

2 被引用数 (Scopus)

抄録

Due to the spread of the Internet and improvement of the audio compression technology, we need technologies to handle a large number of audio files. Separating singing voice from music is one of them and it is used in many applications, such as lyric retrieval and singer recognition. Recently, robust principal component analysis (RPCA) has been proposed, which makes use of repetition of a phrase in an accompaniment. We assume that there are some points to be improved in RPCA. In this paper, we propose a developed method based on the RPCA algorithm. First, we propose the extended RPCA algorithm that makes use of the two features of the spectrogram. Second, we apply simple post-processing to remove noise effectively. Lastly, we experiment our algorithm using the MIR-1K dataset and confirm that the proposed algorithm shows better separation performance than the conventional RPCA method.

本文言語English
ホスト出版物のタイトル2016 IEEE 59th International Midwest Symposium on Circuits and Systems, MWSCAS 2016
出版社Institute of Electrical and Electronics Engineers Inc.
ISBN(電子版)9781509009169
DOI
出版ステータスPublished - 2016 7月 2
イベント59th IEEE International Midwest Symposium on Circuits and Systems, MWSCAS 2016 - Abu Dhabi, United Arab Emirates
継続期間: 2016 10月 162016 10月 19

出版物シリーズ

名前Midwest Symposium on Circuits and Systems
0
ISSN(印刷版)1548-3746

Other

Other59th IEEE International Midwest Symposium on Circuits and Systems, MWSCAS 2016
国/地域United Arab Emirates
CityAbu Dhabi
Period16/10/1616/10/19

ASJC Scopus subject areas

  • 電子材料、光学材料、および磁性材料
  • 電子工学および電気工学

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