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| Presentation | 2021-06-19 13:00 Low Loss Machine Learning for Digital Modeling of Distortion Stomp Boxes. Yuto Matsunaga, Naofumi Aoki, Yoshinori Dobashi (Hokkaido Univ.), Tetsuya Kojima (NITTC)  SP2021-11 |
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| Abstract | (in Japanese) | (See Japanese page) |
| (in English) | Distortion stomp boxes are one of the acoustic devices used on electric guitars. This device has attracted the interest of many guitarists. With the development of digital signal processing technology, a variety of acoustic devices are modeled in digital signal processing. However, distortion stomp boxes are difficult to model due to their nonlinearity. Therefore, research to improve the accuracy of the distortion stomp boxes has been widely conducted. With the recent development of machine learning technology, machine learning is used for modeling of distortion stomp boxes. In this study, we propose a technique based on Long Short-Term Memory (LSTM). The learning model of the proposed technique is constructed using a structure based on the Wiener model. In this paper, after explaining the proposed technique, we compare the proposed technique with a conventional technique that also uses LSTM, and report the results. | |
| Keyword | (in Japanese) | (See Japanese page) |
| (in English) | Distortion stomp boxes / VA Modeling / Machine Learning / LSTM / / / / | |
| Reference Info. | IEICE Tech. Rep., vol. 121, no. 66, SP2021-11, pp. 46-50, June 2021. | |
| Paper # | SP2021-11 | |
| Date of Issue | 2021-06-11 (SP) | |
| ISSN | Online edition: ISSN 2432-6380 | |
| Copyright and reproduction |
All rights are reserved and no part of this publication may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopy, recording, or any information storage and retrieval system, without permission in writing from the publisher. Notwithstanding, instructors are permitted to photocopy isolated articles for noncommercial classroom use without fee. (License No.: 10GA0019/12GB0052/13GB0056/17GB0034/18GB0034) | |
| Download PDF | SP2021-11 |
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| Conference Information | |
| Committee | SP IPSJ-SLP IPSJ-MUS |
| Conference Date | 2021-06-18 - 2021-06-19 |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | Online |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | OTOGAKU Symposium 2021 |
| Paper Information | |
| Registration To | SP |
| Conference Code | 2021-06-SP-SLP-MUS |
| Language | Japanese |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | Low Loss Machine Learning for Digital Modeling of Distortion Stomp Boxes. |
| Sub Title (in English) | |
| Keyword(1) | Distortion stomp boxes |
| Keyword(2) | VA Modeling |
| Keyword(3) | Machine Learning |
| Keyword(4) | LSTM |
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| 1st Author's Name | Yuto Matsunaga |
| 1st Author's Affiliation | Hokkaido University (Hokkaido Univ.) |
| 2nd Author's Name | Naofumi Aoki |
| 2nd Author's Affiliation | Hokkaido University (Hokkaido Univ.) |
| 3rd Author's Name | Yoshinori Dobashi |
| 3rd Author's Affiliation | Hokkaido University (Hokkaido Univ.) |
| 4th Author's Name | Tetsuya Kojima |
| 4th Author's Affiliation | National Institute of Technology, Tokyo College (NITTC) |
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| Speaker | Author-1 |
| Date Time | 2021-06-19 13:00:00 |
| Presentation Time | 120 minutes |
| Registration for | SP |
| Paper # | SP2021-11 |
| Volume (vol) | vol.121 |
| Number (no) | no.66 |
| Page | pp.46-50 |
| #Pages | 5 |
| Date of Issue | 2021-06-11 (SP) |
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