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| Paper Abstract and Keywords | ||
| Presentation | 2017-03-21 16:50 On Data Extension For Signal Data Shu Eguchi, Masaru Tanaka, Jun Fujiki (Fukuoka Univ.), Takio Kurita (Hiroshima Univ.)  BioX2016-73 PRMU2016-236 |
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| Abstract | (in Japanese) | (See Japanese page) |
| (in English) | Efficient learning using limited data in machine learning is also important now even in the era of big data. In the case of image identification, data expansion such as parallel movement, specular inversion, coloring or the like is performed based on the original sample to increase variations and increase the number of data. In this research, we extend data to musical instrument sound data. Specifically, the instrument sound is converted into an image graphically represented by the reproduction time and the sample frequency, and the data is expanded by coloring the image. By coloring, it is possible to obtain as much information as simply being expanded to 3 ch than the original signal data. Then, learning is performed using GoogLeNet implemented by Chainer which is a deep learning tool using this extended data as input data. With this system, learning to recognize a musical instrument from instrumental sounds created with three kinds of instruments such as flute, oboe and fagott, it is possible to expand data similar to image identification even for signal processing confirmed. | |
| Keyword | (in Japanese) | (See Japanese page) |
| (in English) | instrument sound / musical chord / signal processing / image recognition / chainer / ata extension / / | |
| Reference Info. | IEICE Tech. Rep., vol. 116, no. 528, PRMU2016-236, pp. 237-242, March 2017. | |
| Paper # | PRMU2016-236 | |
| Date of Issue | 2017-03-13 (BioX, PRMU) | |
| ISSN | Print edition: ISSN 0913-5685 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 | BioX2016-73 PRMU2016-236 |
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| Conference Information | |
| Committee | PRMU BioX |
| Conference Date | 2017-03-20 - 2017-03-21 |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | |
| Paper Information | |
| Registration To | PRMU |
| Conference Code | 2017-03-PRMU-BioX |
| Language | Japanese |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | On Data Extension For Signal Data |
| Sub Title (in English) | |
| Keyword(1) | instrument sound |
| Keyword(2) | musical chord |
| Keyword(3) | signal processing |
| Keyword(4) | image recognition |
| Keyword(5) | chainer |
| Keyword(6) | ata extension |
| Keyword(7) | |
| Keyword(8) | |
| 1st Author's Name | Shu Eguchi |
| 1st Author's Affiliation | Fukuoka University (Fukuoka Univ.) |
| 2nd Author's Name | Masaru Tanaka |
| 2nd Author's Affiliation | Fukuoka University (Fukuoka Univ.) |
| 3rd Author's Name | Jun Fujiki |
| 3rd Author's Affiliation | Fukuoka University (Fukuoka Univ.) |
| 4th Author's Name | Takio Kurita |
| 4th Author's Affiliation | Hiroshima University (Hiroshima Univ.) |
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| Speaker | Author-1 |
| Date Time | 2017-03-21 16:50:00 |
| Presentation Time | 25 minutes |
| Registration for | PRMU |
| Paper # | BioX2016-73, PRMU2016-236 |
| Volume (vol) | vol.116 |
| Number (no) | no.527(BioX), no.528(PRMU) |
| Page | pp.237-242 |
| #Pages | 6 |
| Date of Issue | 2017-03-13 (BioX, PRMU) |
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