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Committee Date Time Place Paper Title / Authors Abstract Paper #
SP, IPSJ-SLP, IPSJ-MUS 2021-06-19
13:00		 Online Online Low Loss Machine Learning for Digital Modeling of Distortion Stomp Boxes.
Yuto Matsunaga, Naofumi Aoki, Yoshinori Dobashi (Hokkaido Univ.), Tetsuya Kojima (NITTC) SP2021-11		 Distortion stomp boxes are one of the acoustic devices used on electric guitars. This device has attracted the interest ... [more] SP2021-11
pp.46-50
SP, EA, SIP 2020-03-02
13:00		 Okinawa Okinawa Industry Support Center
(Cancelled but technical report was issued)		 [Poster Presentation] High-precision modeling of distortion stomp box by deep learning using spectral features
Kento Yoshimoto, Daichi Kitahara, Akira Hirabayashi (Ritsumeikan Univ.) EA2019-124 SIP2019-126 SP2019-73		 We propose a method for modeling distortion stomp box with high accuracy using a deep neural network, WaveNet. The conve... [more] EA2019-124 SIP2019-126 SP2019-73
pp.135-140
EA, ASJ-H, ASJ-AA 2019-07-16
10:50		 Hokkaido SAPPORO COMMUNITY PLAZA Black Box Modeling of Distortion Stomp Boxes Using Machine Learning
Yuto Matsunaga, Naofumi Aoki, Yoshinori Dobashi (Hokkaidou Univ.), Tetsuya Kojima (NITTC) EA2019-3		 The study of digital modeling for analog circuits has widely been investigate before. The guitar attachment is no except... [more] EA2019-3
pp.9-14
EA, ASJ-H, ASJ-AA 2018-07-25
15:20		 Hokkaido Hokkaido Univ. Digital Modeling of Distortion Effect Using LSTM Machine-Learning
Yuto Matsunaga, Naofumi Aoki, Yoshinori Dobashi, Tsuyoshi Yamamoto (Hokkaido Univ.) EA2018-26		 This paper describes an experimental approach of modeling stomp boxes based on a machine learning
approach. Our propose... [more]		 EA2018-26
pp.153-157
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