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| Presentation | 2020-02-17 09:55 Facilitator Identification Using Multimodal Information in Multi-party Conversation Kouki Honda, Tukasa Shiota, Kazutaka Shimada, Takeshi Saitoh (Kyutech)  NLC2019-41 |
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| Abstract | (in Japanese) | (See Japanese page) |
| (in English) | Predicting roles of participants in a conversation is one of the most important tasks for conversation understanding. In this paper, we propose a prediction model of facilitators in conversations. A previous study has handled verbal features for the facilitator prediction task. However, non-verbal features are also important elements for the prediction. Therefore, we introduce non-verbal features into the prediction model. We utilize two types of non-verbal features: motion features and voice features. The motion features are based on face information and body information. The voice features are based on prosodic information. In the experiment, we compare our model with a verbal feature-based model. The experimental result shows the effectiveness of our method. | |
| Keyword | (in Japanese) | (See Japanese page) |
| (in English) | Multi-party Conversation / Multimodal / Role Recognition / Facilitator / / / / | |
| Reference Info. | IEICE Tech. Rep., vol. 119, no. 415, NLC2019-41, pp. 27-32, Feb. 2020. | |
| Paper # | NLC2019-41 | |
| Date of Issue | 2020-02-09 (NLC) | |
| 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 | NLC2019-41 |
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| Conference Information | |
| Committee | NLC |
| Conference Date | 2020-02-16 - 2020-02-17 |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | Seikei University |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | Integration of verbal and non-verbal information |
| Paper Information | |
| Registration To | NLC |
| Conference Code | 2020-02-NLC |
| Language | Japanese |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | Facilitator Identification Using Multimodal Information in Multi-party Conversation |
| Sub Title (in English) | |
| Keyword(1) | Multi-party Conversation |
| Keyword(2) | Multimodal |
| Keyword(3) | Role Recognition |
| Keyword(4) | Facilitator |
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| Keyword(8) | |
| 1st Author's Name | Kouki Honda |
| 1st Author's Affiliation | Kyushu Institute of Technology (Kyutech) |
| 2nd Author's Name | Tukasa Shiota |
| 2nd Author's Affiliation | Kyushu Institute of Technology (Kyutech) |
| 3rd Author's Name | Kazutaka Shimada |
| 3rd Author's Affiliation | Kyushu Institute of Technology (Kyutech) |
| 4th Author's Name | Takeshi Saitoh |
| 4th Author's Affiliation | Kyushu Institute of Technology (Kyutech) |
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| Speaker | Author-1 |
| Date Time | 2020-02-17 09:55:00 |
| Presentation Time | 25 minutes |
| Registration for | NLC |
| Paper # | NLC2019-41 |
| Volume (vol) | vol.119 |
| Number (no) | no.415 |
| Page | pp.27-32 |
| #Pages | 6 |
| Date of Issue | 2020-02-09 (NLC) |
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