Toward polyphonic musical instrument identification using example-based sparse representation

Mari Okamura*, Masanori Takehara, Satoshi Tamura, Satoru Hayamizu

*この研究の対応する著者

研究成果: Conference contribution

1 被引用数 (Scopus)

抄録

Musical instrument identification is one of the major topics in music signal processing. In this paper, we propose a musical instrument identification method based on sparse representation for polyphonic sounds. Such the identification has been still categorized into challenging tasks, since it needs high-performance signal processing techniques. The proposed scheme can be applied without any signal processing such as source separation. Sample feature vectors for various musical instruments are used for the base matrix of sparse representation. We conducted two experiments to evaluate the proposed method. First, the musical instrument identification is tested for monophonic sounds using five musical instruments. The average accuracy of 91.9% was obtained and it shows the effectiveness of the proposed method. Second, musical instrument composition of polyphonic sounds is examined, which contain two instruments. It is found that the estimated weight vector by sparse representation indicates the mixture ratio of two instruments.

本文言語English
ホスト出版物のタイトル2012 Conference Handbook - Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2012
出版ステータスPublished - 2012
外部発表はい
イベント2012 4th Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2012 - Hollywood, CA, United States
継続期間: 2012 12 32012 12 6

出版物シリーズ

名前2012 Conference Handbook - Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2012

Other

Other2012 4th Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2012
国/地域United States
CityHollywood, CA
Period12/12/312/12/6

ASJC Scopus subject areas

  • 情報システム

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