Presentation 2021-03-05
Automatic music transcription system based on convolutional neural network for electric guitar considering sounds of same pitch and different strings
Toshiaki Matsui, Tetsuya Matsumoto, Hiroaki Kudo, Yoshinori Takeuchi,
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Abstract(in Japanese) (See Japanese page)
Abstract(in English) In this research, we propose a system that outputs tablature notation of an electric guitar performance from acoustic signals and tempo information. The user of the proposed system records only single note performances for all frets on each string as training data in advance. For training this system, we use single note data and chord data created by synthesis of the recorded single notes. We conducted an experiment using actual guitar performances. For monophonic guitar performances, we conducted a comparison experiment with a baseline method that can only estimate single tones combining pitch estimation and string classification. For monophonic guitar performances, the F-value of the proposed method were 0.988 for the pitch estimation and 0.844 for the fret and string position estimation. The proposed method resulted in a higher F-value than the baseline method in fret and string position estimation of monophonic performances. For polyphonic guitar performances, the F-value of the proposed method were 0.939 for the pitch estimation and 0.780 for the fret and string position estimation. The proposed method achieved a relatively high F-value without recording chord data.
Keyword(in Japanese) (See Japanese page)
Keyword(in English) automatic music transcription / convolutional neural network / electric guitar / tablature / string detection
Paper # PRMU2020-86
Date of Issue 2021-02-25 (PRMU)

Conference Information
Committee PRMU / IPSJ-CVIM
Conference Date 2021/3/4(2days)
Place (in Japanese) (See Japanese page)
Place (in English) Online
Topics (in Japanese) (See Japanese page)
Topics (in English) Computer Vision and Pattern Recognition for specific environment
Chair Yoichi Sato(Univ. of Tokyo)
Vice Chair Akisato Kimura(NTT) / Masakazu Iwamura(Osaka Pref. Univ.)
Secretary Akisato Kimura(Mobility Technologies) / Masakazu Iwamura(Chubu Univ.)
Assistant Takashi Shibata(NTT) / Masashi Nishiyama(Tottori Univ.)

Paper Information
Registration To Technical Committee on Pattern Recognition and Media Understanding / Special Interest Group on Computer Vision and Image Media
Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) Automatic music transcription system based on convolutional neural network for electric guitar considering sounds of same pitch and different strings
Sub Title (in English)
Keyword(1) automatic music transcription
Keyword(2) convolutional neural network
Keyword(3) electric guitar
Keyword(4) tablature
Keyword(5) string detection
1st Author's Name Toshiaki Matsui
1st Author's Affiliation Nagoya University(Nagoya Univ)
2nd Author's Name Tetsuya Matsumoto
2nd Author's Affiliation Nagoya University(Nagoya Univ)
3rd Author's Name Hiroaki Kudo
3rd Author's Affiliation Nagoya University(Nagoya Univ)
4th Author's Name Yoshinori Takeuchi
4th Author's Affiliation Daido University(Daido Univ)
Date 2021-03-05
Paper # PRMU2020-86
Volume (vol) vol.120
Number (no) PRMU-409
Page pp.pp.97-102(PRMU),
#Pages 6
Date of Issue 2021-02-25 (PRMU)