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| Presentation | 2018-03-20 09:00 [Poster Presentation] Performance evaluation of unknown sound clustering for indoor-environmental sound classification based on self-generated acoustic model Sakiko Mishima, Yukoh Wakabayashi, Takahiro Fukumori, Keisuke Imoto, Masato Nakayama, Takanobu Nishiura (Ritsumeikan Univ.)  EA2017-152 SIP2017-161 SP2017-135 |
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| Abstract | (in Japanese) | (See Japanese page) |
| (in English) | Indoor-environmental sound classification is useful for surveillance systems which monitor the situations in the dark and blind areas. In previous research, the acoustic model has been constructed to classify the sounds. However, this approach incorrectly classifies unknown-class sound into known-class one. We then focus on a classification method with an self-generated acoustic model to prevent such misclassification. The model is constructed using the sounds which are classified into unknown-class by known/unknown sound classification method. In this paper, we propose a clustering method using output probability distributions of deep neural network. To confirm the performance of unknown sound clustering, we carried out the evaluation experiment. |
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| Keyword | (in Japanese) | (See Japanese page) |
| (in English) | Environmental sound classification / Self-generated acoustic model / Deep neural network / Clustering / / / / | |
| Reference Info. | IEICE Tech. Rep., vol. 117, no. 516, SIP2017-161, pp. 277-280, March 2018. | |
| Paper # | SIP2017-161 | |
| Date of Issue | 2018-03-12 (EA, SIP, SP) | |
| 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 | EA2017-152 SIP2017-161 SP2017-135 |
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| Conference Information | |
| Committee | SIP EA SP MI |
| Conference Date | 2018-03-19 - 2018-03-20 |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | Speech, Engineering/Electro Acoustics, Signal Processing, and Related Topics [SIP, EA, SP]/ Medical Image Engineering, Analysis, Recognition, etc. [MI] |
| Paper Information | |
| Registration To | SIP |
| Conference Code | 2018-03-SIP-EA-SP-MI |
| Language | Japanese |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | Performance evaluation of unknown sound clustering for indoor-environmental sound classification based on self-generated acoustic model |
| Sub Title (in English) | |
| Keyword(1) | Environmental sound classification |
| Keyword(2) | Self-generated acoustic model |
| Keyword(3) | Deep neural network |
| Keyword(4) | Clustering |
| Keyword(5) | |
| Keyword(6) | |
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| 1st Author's Name | Sakiko Mishima |
| 1st Author's Affiliation | Ritsumeikan University (Ritsumeikan Univ.) |
| 2nd Author's Name | Yukoh Wakabayashi |
| 2nd Author's Affiliation | Ritsumeikan University (Ritsumeikan Univ.) |
| 3rd Author's Name | Takahiro Fukumori |
| 3rd Author's Affiliation | Ritsumeikan University (Ritsumeikan Univ.) |
| 4th Author's Name | Keisuke Imoto |
| 4th Author's Affiliation | Ritsumeikan University (Ritsumeikan Univ.) |
| 5th Author's Name | Masato Nakayama |
| 5th Author's Affiliation | Ritsumeikan University (Ritsumeikan Univ.) |
| 6th Author's Name | Takanobu Nishiura |
| 6th Author's Affiliation | Ritsumeikan University (Ritsumeikan Univ.) |
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| Speaker | Author-1 |
| Date Time | 2018-03-20 09:00:00 |
| Presentation Time | 90 minutes |
| Registration for | SIP |
| Paper # | EA2017-152, SIP2017-161, SP2017-135 |
| Volume (vol) | vol.117 |
| Number (no) | no.515(EA), no.516(SIP), no.517(SP) |
| Page | pp.277-280 |
| #Pages | 4 |
| Date of Issue | 2018-03-12 (EA, SIP, SP) |
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