Paper Abstract and Keywords |
Presentation |
2021-05-27 09:50
Investigation and Evaluation Experiment of Noise Removal for Voice Recognition in Specific Noisy Environment Shota Sano, Fumitaka Murakami, Yuusuke Kawakita, Tsuyoshi Miyazaki, Hiroshi Tanaka (KAIT) SeMI2021-2 |
Abstract |
(in Japanese) |
(See Japanese page) |
(in English) |
In this manuscript, the noise removal performance and speech recognition accuracy is described when noise is removed by assuming the specific situation in order to improve speech recognition accuracy in a noisy environment such as a crowded spot or in a train. Noise removal was performed by using the SS and DAE method in the experiment. We created speech data with noise superimposed with 2 types of noise assuming crowded spot and inside a train, and 6 types of SN ratio of -10, -5, 0, 5, 10, 15 dB. In the DAE method, the noise was removed and compared by using the model created by mixing multiple noises, and learning models individually created by adding each noise with SN condition. The noise removal performance was evaluated by the cosine similarity to the time-series data, the similarity of the spectrogram image by the normalized correlation, and the speech recognition accuracy between speech data before noise superimposition and the noise removal. It was verified that the individual learning model gave better results than the results by the model created by mixing noise. Also it was confirmed that speech recognition was possible with an accuracy of about 80% only for the model individually created under the conditions of SN ratio of 10dB. |
Keyword |
(in Japanese) |
(See Japanese page) |
(in English) |
Deep Learning / Voice Recognition / Noise Removal / DAE / Spectral Subtraction / / / |
Reference Info. |
IEICE Tech. Rep., vol. 121, no. 41, SeMI2021-2, pp. 5-10, May 2021. |
Paper # |
SeMI2021-2 |
Date of Issue |
2021-05-20 (SeMI) |
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) |
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SeMI2021-2 |
Conference Information |
Committee |
SeMI IPSJ-MBL IPSJ-DPS IPSJ-ITS |
Conference Date |
2021-05-27 - 2021-05-28 |
Place (in Japanese) |
(See Japanese page) |
Place (in English) |
Online |
Topics (in Japanese) |
(See Japanese page) |
Topics (in English) |
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Paper Information |
Registration To |
SeMI |
Conference Code |
2021-05-SeMI-MBL-DPS-ITS |
Language |
Japanese |
Title (in Japanese) |
(See Japanese page) |
Sub Title (in Japanese) |
(See Japanese page) |
Title (in English) |
Investigation and Evaluation Experiment of Noise Removal for Voice Recognition in Specific Noisy Environment |
Sub Title (in English) |
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Keyword(1) |
Deep Learning |
Keyword(2) |
Voice Recognition |
Keyword(3) |
Noise Removal |
Keyword(4) |
DAE |
Keyword(5) |
Spectral Subtraction |
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1st Author's Name |
Shota Sano |
1st Author's Affiliation |
Kanagawa Institute of Technology (KAIT) |
2nd Author's Name |
Fumitaka Murakami |
2nd Author's Affiliation |
Kanagawa Institute of Technology (KAIT) |
3rd Author's Name |
Yuusuke Kawakita |
3rd Author's Affiliation |
Kanagawa Institute of Technology (KAIT) |
4th Author's Name |
Tsuyoshi Miyazaki |
4th Author's Affiliation |
Kanagawa Institute of Technology (KAIT) |
5th Author's Name |
Hiroshi Tanaka |
5th Author's Affiliation |
Kanagawa Institute of Technology (KAIT) |
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Speaker |
Author-1 |
Date Time |
2021-05-27 09:50:00 |
Presentation Time |
20 minutes |
Registration for |
SeMI |
Paper # |
SeMI2021-2 |
Volume (vol) |
vol.121 |
Number (no) |
no.41 |
Page |
pp.5-10 |
#Pages |
6 |
Date of Issue |
2021-05-20 (SeMI) |
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