Parametric Approximation of Piano Sound Based on Kautz Model with Sparse Linear Prediction

Kenji Kobayashi, Daiki Takeuchi, Mio Iwamoto, Kohei Yatabe, Yasuhiro Oikawa

    研究成果: Conference contribution

    3 被引用数 (Scopus)

    抄録

    The piano is one of the most popular and attractive musical instruments that leads to a lot of research on it. To synthesize the piano sound in a computer, many modeling methods have been proposed from full physical models to approximated models. The focus of this paper is on the latter, approximating piano sound by an IIR filter. For stably estimating parameters, the Kautz model is chosen as the filter structure. Then, the selection of poles and excitation signal rises as the questions which are typical to the Kautz model that must be solved. In this paper, sparsity based construction of the Kautz model is proposed for approximating piano sound.

    本文言語English
    ホスト出版物のタイトル2018 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2018 - Proceedings
    出版社Institute of Electrical and Electronics Engineers Inc.
    ページ626-630
    ページ数5
    2018-April
    ISBN(印刷版)9781538646588
    DOI
    出版ステータスPublished - 2018 9 10
    イベント2018 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2018 - Calgary, Canada
    継続期間: 2018 4 152018 4 20

    Other

    Other2018 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2018
    CountryCanada
    CityCalgary
    Period18/4/1518/4/20

    ASJC Scopus subject areas

    • Software
    • Signal Processing
    • Electrical and Electronic Engineering

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