Ranking Conversations based on Rapport in First Meeting Conversations and Friend Conversations
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- HAYASHI Takato
- Japan Advanced Institute of Science and Technology
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- KIMURA Ryusei
- Japan Advanced Institute of Science and Technology
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- ISHII Ryo
- NTT Human Informatics Laboratories
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- NIHEI Fumio
- NTT Human Informatics Laboratories
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- FUKAYAMA Atsushi
- NTT Human Informatics Laboratories
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- OKADA Shogo
- Japan Advanced Institute of Science and Technology
Bibliographic Information
- Other Title
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- 初対面会話と友人会話におけるラポールに基づく会話の順序付け
Description
<p>Rapport is a harmonious relationship with others. We aim to automatically estimate a speaker's subjective rapport using their nonverbal behavior during a conversation. Rapport estimation is generally formulated as a regression. However, it is difficult to learn a mapping between nonverbal behaviors and rapport ratings during a conversation because of individual differences in rapport ratings. To alleviate this problem, we formulate rapport estimation as learning to rank. Learning to rank avoids the problem of individual differences in rapport ratings using preference learning, which learns the ordinal relationship between two conversations based on rapport reported by the same user. To evaluate the proposed method, we used a dataset consisting of first-meeting conversations and friend conversations that includes subjective rapport ratings. We compared the proposed model with the regression model using metrics for ranking. The result indicates that the proposed model is more suitable than the regression model for rapport estimations. </p>
Journal
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- JSAI Technical Report, SIG-SLUD
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JSAI Technical Report, SIG-SLUD 98 (0), 72-79, 2023-08-25
The Japanese Society for Artificial Intelligence
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Details 詳細情報について
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- CRID
- 1390578702994843904
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- ISSN
- 24364576
- 09185682
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- Text Lang
- ja
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- Data Source
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- JaLC
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- Abstract License Flag
- Allowed