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| Presentation | 2024-02-29 10:30 Multi-task learning with age information model for highly accurate elderly speech recognition. Shine Takumi, Kinouchi Takahiro, Wakabayashi Yukoh, Kitaoka Norihide (TUT)  EA2023-64 SIP2023-111 SP2023-46 |
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| Abstract | (in Japanese) | (See Japanese page) |
| (in English) | The speech recognition of the elderly is less accurate, especially in smart speaker speech recognition, due to aging-related factors such as vocal organ deterioration, increased pauses, and decreased speech rate, leading to differences in acoustic features. Challenges include difficulty in recording elderly speech and limited data availability. The aim of this study is to enhance the accuracy of elderly speech recognition. As a proposed method, we built two models: one integrating age estimation into the speech recognition model and another employing adversarial multitask learning with GAN framework. Comparing the accuracy of these models revealed improved recognition for both elderly and general adult speech, demonstrating the effectiveness of the multitasking approach. | |
| Keyword | (in Japanese) | (See Japanese page) |
| (in English) | Elderly Speech / Speech Recognition / Multi-task Learning / Adversarial Multi-task Learning / / / / | |
| Reference Info. | IEICE Tech. Rep., vol. 123, no. 403, SP2023-46, pp. 19-24, Feb. 2024. | |
| Paper # | SP2023-46 | |
| Date of Issue | 2024-02-22 (EA, SIP, 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 | EA2023-64 SIP2023-111 SP2023-46 |
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| Conference Information | |
| Committee | SIP SP EA IPSJ-SLP |
| Conference Date | 2024-02-29 - 2024-03-01 |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | |
| Paper Information | |
| Registration To | SP |
| Conference Code | 2024-02-SIP-SP-EA-SLP |
| Language | Japanese |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | Multi-task learning with age information model for highly accurate elderly speech recognition. |
| Sub Title (in English) | |
| Keyword(1) | Elderly Speech |
| Keyword(2) | Speech Recognition |
| Keyword(3) | Multi-task Learning |
| Keyword(4) | Adversarial Multi-task Learning |
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| 1st Author's Name | Shine Takumi |
| 1st Author's Affiliation | Toyohashi University of Technology (TUT) |
| 2nd Author's Name | Kinouchi Takahiro |
| 2nd Author's Affiliation | Toyohashi University of Technology (TUT) |
| 3rd Author's Name | Wakabayashi Yukoh |
| 3rd Author's Affiliation | Toyohashi University of Technology (TUT) |
| 4th Author's Name | Kitaoka Norihide |
| 4th Author's Affiliation | Toyohashi University of Technology (TUT) |
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| Speaker | Author-1 |
| Date Time | 2024-02-29 10:30:00 |
| Presentation Time | 20 minutes |
| Registration for | SP |
| Paper # | EA2023-64, SIP2023-111, SP2023-46 |
| Volume (vol) | vol.123 |
| Number (no) | no.401(EA), no.402(SIP), no.403(SP) |
| Page | pp.19-24 |
| #Pages | 6 |
| Date of Issue | 2024-02-22 (EA, SIP, SP) |
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