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A multimodal multiparty human-robot dialogue corpus for real world interaction
https://doi.org/10.15084/00001915
https://doi.org/10.15084/00001915112ad785-c4ad-49cc-a68f-d9ea36cfe8a5
| 名前 / ファイル | ライセンス | アクション |
|---|---|---|
lrec2018sss_funakoshi.pdf (1.5 MB)
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| Item type | 会議発表論文 / Conference Paper(1) | |||||
|---|---|---|---|---|---|---|
| 公開日 | 2019-03-06 | |||||
| タイトル | ||||||
| タイトル | A multimodal multiparty human-robot dialogue corpus for real world interaction | |||||
| 言語 | en | |||||
| 言語 | ||||||
| 言語 | eng | |||||
| キーワード | ||||||
| 言語 | en | |||||
| 主題Scheme | Other | |||||
| 主題 | human-robot interaction | |||||
| キーワード | ||||||
| 言語 | en | |||||
| 主題Scheme | Other | |||||
| 主題 | verbal and non-verbal communication | |||||
| キーワード | ||||||
| 言語 | en | |||||
| 主題Scheme | Other | |||||
| 主題 | social signal processing | |||||
| 資源タイプ | ||||||
| 資源タイプ識別子 | http://purl.org/coar/resource_type/c_5794 | |||||
| 資源タイプ | conference paper | |||||
| ID登録 | ||||||
| ID登録 | 10.15084/00001915 | |||||
| ID登録タイプ | JaLC | |||||
| 著者 |
Funakoshi, Kotaro
× Funakoshi, Kotaro |
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| 著者所属(英) | ||||||
| 内容記述タイプ | Other | |||||
| 内容記述 | Kyoto University/Honda Research Institute Japan Co.,Ltd. | |||||
| 会議概要（会議名, 開催地, 会期, 主催者等） | ||||||
| 内容記述タイプ | Other | |||||
| 内容記述 | LREC 2018 Special Speech Sessions "Speech Resources Collection in Real-World Situations"; Phoenix Seagaia Conference Center, Miyazaki; 2018-05-09 | |||||
| 抄録(英) | ||||||
| 内容記述タイプ | Other | |||||
| 内容記述 | We have developed the MPR multimodal dialogue corpus and describe research activities using the corpus aimed for enabling multiparty human-robot verbal communication in real-world settings. While aiming for that as the final goal, the immediate focus of our project and the corpus is non-verbal communication, especially social signal processing by machines as the foundation of human-machine verbal communication. The MPR corpus stores annotated audio-visual recordings of dialogues between one robot and one or multiple (up to tree) participants. The annotations include speech segment, addressee of speech, transcript, interaction state, and, dialogue act types. Our research on multiparty dialogue management, boredom recognition, response obligation recognition, surprise detection and repair detection using the corpus is briefly introduced, and an analysis on repair in multiuser situations is presented. It exhibits richer repair behaviors and demands more sophisticated repair handling by machines. | |||||
| 書誌情報 |
en : Proceedings of the LREC 2018 Special Speech Sessions p. 35-39, 発行日 2018-05-09 |
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| フォーマット | ||||||
| 内容記述タイプ | Other | |||||
| 内容記述 | application/pdf | |||||
| 著者版フラグ | ||||||
| 出版タイプ | VoR | |||||
| 出版タイプResource | http://purl.org/coar/version/c_970fb48d4fbd8a85 | |||||
| 出版者 | ||||||
| 出版者 | Center for Corpus Development, National Institute for Japanese Language and Linguistics | |||||
