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1
A Multimodal Model for Predicting Conversational Feedbacks
In: Text, Speech, and Dialogue 24th International Conference, TSD 2021, Olomouc, Czech Republic, September 6–9, 2021, Proceedings ; International Conference on Text, Speech, and Dialogue (TSD ) ; https://hal.archives-ouvertes.fr/hal-03331446 ; International Conference on Text, Speech, and Dialogue (TSD ), 2021, Olomouc, Czech Republic. ⟨10.1007/978-3-030-83527-9_46⟩ (2021)
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2
Two-level classification for dialogue act recognition in task-oriented dialogues
In: COLING-2020 ; https://hal.archives-ouvertes.fr/hal-02954413 ; COLING-2020, Oct 2020, Barcelona, Spain (2020)
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3
Toward an Automatic Prediction of the Sense of Presence in Virtual Reality Environment
In: 6th International Conference on Human-Agent Interaction (HAI-2018) ; https://hal.archives-ouvertes.fr/hal-01907590 ; 6th International Conference on Human-Agent Interaction (HAI-2018), Dec 2018, Southampton, United Kingdom ; http://hai-conference.net/hai2018/ (2018)
Abstract: International audience ; In human-agent interaction, one key challenge is the evaluation of the user's experience. In the virtual reality domain, the sense of presence and co-presence, reflecting the psychological immersion of the user, is generally assessed through well-grounded subjective post-experience questionnaires. In this article, we aim at presenting a new way to automatically predict the sense of presence and co-presence of a user at the end of an interaction based on specific verbal and non-verbal behavioral cues automatically computed. A random forest algorithm has been applied on a human-agent interaction corpus collected in the specific context of a virtual environment developed to train doctors to break bad news to a virtual patient. The performance of the models demonstrate the capacity to automatically and accurately predict the level of presence and co-presence, but also show the relevancy of the verbal and non-verbal behavioral cues as objective measures of presence.
Keyword: [INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI]; [INFO.INFO-GR]Computer Science [cs]/Graphics [cs.GR]; [INFO.INFO-HC]Computer Science [cs]/Human-Computer Interaction [cs.HC]; [INFO.INFO-TT]Computer Science [cs]/Document and Text Processing; [SCCO.LING]Cognitive science/Linguistics; [SDV.NEU.SC]Life Sciences [q-bio]/Neurons and Cognition [q-bio.NC]/Cognitive Sciences; Sense of Presence; Virtual Patient; Virtual Reality
URL: https://hal.archives-ouvertes.fr/hal-01907590/document
https://hal.archives-ouvertes.fr/hal-01907590
https://hal.archives-ouvertes.fr/hal-01907590/file/HAI-Ochs-HAL.pdf
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4
What common ground between a human and a virtual agent? The case of task-oriented dialogues for breaking bad news
In: SEMDIAL ; https://hal.archives-ouvertes.fr/hal-01907596 ; SEMDIAL, Nov 2018, Aix-en-Provence, France (2018)
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5
The Acorformed Corpus: Investigating Multimodality in Human-Human and Human-Virtual Patient Interactions
In: CLARIN-2018 ; https://hal.archives-ouvertes.fr/hal-01907582 ; CLARIN-2018, Oct 2018, Pisa, Italy (2018)
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6
Virtual Patient for Training Doctors to Break Bad News
In: Actes du Workshop Affect, Compagnon Artificiel Interaction, WACAI'2016 ; Workshop, Affect, Compagnon Artificiel, Interaction ; https://hal.archives-ouvertes.fr/hal-01462159 ; Workshop, Affect, Compagnon Artificiel, Interaction, 2016, Brest, France. non paginé (2016)
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