Paper Abstract and Keywords |
Presentation |
2017-03-14 13:00
Analysis of Coin Falling Sound Using Machine Leaning Wataru Yokota, Yasunari Obuchi (Tokyo Univ Tech) |
Abstract |
(in Japanese) |
(See Japanese page) |
(in English) |
As a method of discriminating invisible part information, there is a hammering test for discriminating an object using a sound signal. In this paper, we deal with coin falling sounds as an example of such sound classification. In conventional coin discrimination studies, humans have been analyzing a single speech feature. However, it is difficult to accurately analyze many speech features by this method. It is necessary to accurately analyze large quantities of features. Combining machine learning with sound signals analysis seems to make it possible to analyze many feature quantities more accurately. For this reason, we analyzed sounds of popular five-yen and ten-yen coins falling into various materials using machine learning. |
Keyword |
(in Japanese) |
(See Japanese page) |
(in English) |
Machine Leaning / Coin / Sound Signal / Feature extraction / / / / |
Reference Info. |
ITE Tech. Rep., vol. 41, pp. 261-264, March 2017. |
Paper # |
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Date of Issue |
2017-03-07 (AIT) |
ISSN |
Print edition: ISSN 1342-6893 Online edition: ISSN 2424-1970 |
Download PDF |
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Conference Information |
Committee |
AIT IIEEJ AS CG-ARTS |
Conference Date |
2017-03-14 - 2017-03-14 |
Place (in Japanese) |
(See Japanese page) |
Place (in English) |
Ochanomizu Univ. |
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(See Japanese page) |
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Paper Information |
Registration To |
AS |
Conference Code |
2017-03-AIT-IIEEJ-AS-ARTS |
Language |
Japanese |
Title (in Japanese) |
(See Japanese page) |
Sub Title (in Japanese) |
(See Japanese page) |
Title (in English) |
Analysis of Coin Falling Sound Using Machine Leaning |
Sub Title (in English) |
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Machine Leaning |
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Coin |
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Sound Signal |
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Feature extraction |
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1st Author's Name |
Wataru Yokota |
1st Author's Affiliation |
Tokyo University of Technology (Tokyo Univ Tech) |
2nd Author's Name |
Yasunari Obuchi |
2nd Author's Affiliation |
Tokyo University of Technology (Tokyo Univ Tech) |
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Speaker |
Author-1 |
Date Time |
2017-03-14 13:00:00 |
Presentation Time |
90 minutes |
Registration for |
AS |
Paper # |
AIT2017-119 |
Volume (vol) |
vol.41 |
Number (no) |
no.12 |
Page |
pp.261-264 |
#Pages |
4 |
Date of Issue |
2017-03-07 (AIT) |