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| Presentation | 2023-11-17 09:20 Co-speech Gesture Generation with Variational Auto Encoder Shihichi Ka, Koichi Shinoda (Tokyo Tech)  PRMU2023-29 |
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| Abstract | (in Japanese) | (See Japanese page) |
| (in English) | Co-speech gesture generation is the study of generating gestures from speech. In prior works, deterministic methods learn a one-to-one mapping between speech and motion, and probabilistic methods model the probability of motions. While the former can infer the motion corresponding to the speech, it only generates one motion. In contrast, the latter can generate many motions, but it generates motions that don't match the speech. In this paper, we will propose the probabilistic method by training VAE with the speaker's information and randomizing it. Consequently, the fidelity of VAE is improved, and it can generate more diverse motions. |
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| Keyword | (in Japanese) | (See Japanese page) |
| (in English) | Co-speech gesture generation, / Human motion synthesis / Variational auto encoder / Pre-training / Skeleton / Graph Convolutional Neural Network / / | |
| Reference Info. | IEICE Tech. Rep., vol. 123, no. 266, PRMU2023-29, pp. 74-79, Nov. 2023. | |
| Paper # | PRMU2023-29 | |
| Date of Issue | 2023-11-09 (PRMU) | |
| 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 | PRMU2023-29 |
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| Conference Information | |
| Committee | PRMU IPSJ-CVIM IPSJ-DCC IPSJ-CGVI |
| Conference Date | 2023-11-16 - 2023-11-17 |
| 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 | 2023-11-PRMU-CVIM-DCC-CGVI |
| Language | Japanese |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | Co-speech Gesture Generation with Variational Auto Encoder |
| Sub Title (in English) | |
| Keyword(1) | Co-speech gesture generation, |
| Keyword(2) | Human motion synthesis |
| Keyword(3) | Variational auto encoder |
| Keyword(4) | Pre-training |
| Keyword(5) | Skeleton |
| Keyword(6) | Graph Convolutional Neural Network |
| Keyword(7) | |
| Keyword(8) | |
| 1st Author's Name | Shihichi Ka |
| 1st Author's Affiliation | Tokyo Institute of Technology (Tokyo Tech) |
| 2nd Author's Name | Koichi Shinoda |
| 2nd Author's Affiliation | Tokyo Institute of Technology (Tokyo Tech) |
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| Speaker | Author-1 |
| Date Time | 2023-11-17 09:20:00 |
| Presentation Time | 90 minutes |
| Registration for | PRMU |
| Paper # | PRMU2023-29 |
| Volume (vol) | vol.123 |
| Number (no) | no.266 |
| Page | pp.74-79 |
| #Pages | 6 |
| Date of Issue | 2023-11-09 (PRMU) |
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