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| Presentation | 2020-03-06 10:10 A Comparison Study of Neural Sign Language Translation Methods with Spatio-Temporal Features Kodai Watanabe, Wataru Kameyama (Waseda Univ.)  IMQ2019-68 IE2019-150 MVE2019-89 |
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| Abstract | (in Japanese) | (See Japanese page) |
| (in English) | In Neural Sign Language Translation, a model based on 2DCNN (2 Dimensional Convolutional Neural Network) called AlexNet and a neural machine translation model called Seq2Seq has been proposed. In this model, temporal information is extracted by GRU (Gated Recurrent Unit) from the features in which the spatial information is lost by 2DCNN. However, since sign language uses position, shape and motion of hands and fingers, a model that can extract temporal information from the features that contain spatial information seems to be more suitable. Therefore, in this paper, we propose various methods and compare them that extract temporal information at the stage of extracting spatial features from each frame of video. As the result of the comparison experiment of the various spatio-temporal feature extractors, it is suggested that the number of to-be-optimized parameters and the performance of sign language translation are inversely proportional on the dataset used in this experiment. That seems the reason why the model using only Optical Flow shows the highest performance in sign language translation because it has the least number of parameters to be trained. | |
| Keyword | (in Japanese) | (See Japanese page) |
| (in English) | Neural Sign Language Translation / Spatio-temporal Features / DNN / Optical Flow / / / / | |
| Reference Info. | IEICE Tech. Rep., vol. 119, no. 456, IE2019-150, pp. 273-278, March 2020. | |
| Paper # | IE2019-150 | |
| Date of Issue | 2020-02-27 (IMQ, IE, MVE) | |
| 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 | IMQ2019-68 IE2019-150 MVE2019-89 |
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| Conference Information | |
| Committee | IE IMQ MVE CQ |
| Conference Date | 2020-03-05 - 2020-03-06 |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | Kyushu Institute of Technology |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | |
| Paper Information | |
| Registration To | IE |
| Conference Code | 2020-03-IE-IMQ-MVE-CQ |
| Language | Japanese |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | A Comparison Study of Neural Sign Language Translation Methods with Spatio-Temporal Features |
| Sub Title (in English) | |
| Keyword(1) | Neural Sign Language Translation |
| Keyword(2) | Spatio-temporal Features |
| Keyword(3) | DNN |
| Keyword(4) | Optical Flow |
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| 1st Author's Name | Kodai Watanabe |
| 1st Author's Affiliation | Waseda University (Waseda Univ.) |
| 2nd Author's Name | Wataru Kameyama |
| 2nd Author's Affiliation | Waseda University (Waseda Univ.) |
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| Speaker | Author-1 |
| Date Time | 2020-03-06 10:10:00 |
| Presentation Time | 25 minutes |
| Registration for | IE |
| Paper # | IMQ2019-68, IE2019-150, MVE2019-89 |
| Volume (vol) | vol.119 |
| Number (no) | no.454(IMQ), no.456(IE), no.457(MVE) |
| Page | pp.273-278 |
| #Pages | 6 |
| Date of Issue | 2020-02-27 (IMQ, IE, MVE) |
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