Multipitch estimation and instrument recognition by exemplar-based sparse representation

Ikuo Degawa, Kei Sato, Masaaki Ikehara

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

    Abstract

    This paper investigates the pitch estimation and the instrument recognition of music signals. A note exemplar is a spectrum segment of notes of the specific pitch and instrument, which is stored as a form of dictionary preliminarily. We describe the method of reconstructing a frame of musical signals as the linear combination of exemplars from the large exemplar dictionary with sparse (l1 minimized) coefficient vector. Reconstruction constraints are imposed to KL divergence of spectra, which is found to produce better results than Euclidean distance. The proposed algorithm shows the ability to transcript music pieces with relatively many notes per a frame and to divide the instrument explicitly through some experiments.

    Original languageEnglish
    Title of host publicationConference Record of the 47th Asilomar Conference on Signals, Systems and Computers
    PublisherIEEE Computer Society
    Pages560-564
    Number of pages5
    ISBN (Print)9781479923908
    DOIs
    Publication statusPublished - 2013 Jan 1
    Event2013 47th Asilomar Conference on Signals, Systems and Computers - Pacific Grove, CA, United States
    Duration: 2013 Nov 32013 Nov 6

    Publication series

    NameConference Record - Asilomar Conference on Signals, Systems and Computers
    ISSN (Print)1058-6393

    Other

    Other2013 47th Asilomar Conference on Signals, Systems and Computers
    CountryUnited States
    CityPacific Grove, CA
    Period13/11/313/11/6

    Keywords

    • instrument recognition
    • l1 regularized minimization
    • note exemplar
    • pitch estimation

    ASJC Scopus subject areas

    • Signal Processing
    • Computer Networks and Communications

    Fingerprint Dive into the research topics of 'Multipitch estimation and instrument recognition by exemplar-based sparse representation'. Together they form a unique fingerprint.

  • Cite this

    Degawa, I., Sato, K., & Ikehara, M. (2013). Multipitch estimation and instrument recognition by exemplar-based sparse representation. In Conference Record of the 47th Asilomar Conference on Signals, Systems and Computers (pp. 560-564). [6810341] (Conference Record - Asilomar Conference on Signals, Systems and Computers). IEEE Computer Society. https://doi.org/10.1109/ACSSC.2013.6810341