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A Generic Machine Learning Based Approach for Addressee Detection In Multiparty Interaction.

, , , , and . IVA, page 119-126. ACM, (2019)

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Impact of adaptive multimodal empathic behavior on the user interaction., , , , and . IVA, page 11:1-11:8. ACM, (2022)Une architecture d'agent conversationnel collaboratif et pédagogique pour les simulations immersives., , and . JFSMA, page 249-250. Cépaduès Éditions, (2016)A novel focus encoding scheme for addressee detection in multiparty interaction using machine learning algorithms., , , and . J. Multimodal User Interfaces, 15 (2): 1-14 (2021)Using Multimodal Information to Enhance Addressee Detection in Multiparty Interaction., , , and . ICAART (1), page 267-274. SciTePress, (2019)A Generic Machine Learning Based Approach for Addressee Detection In Multiparty Interaction., , , , and . IVA, page 119-126. ACM, (2019)Multimodal Analysis of Cohesion in Multi-party Interactions., , , , and . LREC, page 498-507. European Language Resources Association, (2020)Performance Comparison of Machine Learning Models Trained on Manual vs ASR Transcriptions for Dialogue Act Annotation., , , and . ICTAI, page 1013-1017. IEEE, (2018)RoboBreizh, RoboCup@Home SSPL Champion 2022., , , , , , and . RoboCup, volume 13561 of Lecture Notes in Computer Science, page 203-214. Springer, (2022)Multimodal adaptive empathic agent architecture., , , , and . IVA, page 36:1-36:3. ACM, (2022)