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dc.rights.licenseopenen_US
hal.structure.identifierInstitut des Systèmes Intelligents et de Robotique [ISIR]
dc.contributor.authorGALLAND, Lucie
hal.structure.identifierInstitut des Systèmes Intelligents et de Robotique [ISIR]
dc.contributor.authorPELACHAUD, Catherine
hal.structure.identifierSommeil, Addiction et Neuropsychiatrie [Bordeaux] [SANPSY]
dc.contributor.authorPECUNE, Florian
dc.date.accessioned2025-01-08T07:40:48Z
dc.date.available2025-01-08T07:40:48Z
dc.date.issued2024-12-26
dc.date.conference2024-09-16
dc.identifier.urihttps://oskar-bordeaux.fr/handle/20.500.12278/204188
dc.description.abstractEnThe demand for mental health services has outpaced available resources, resulting in long wait times for patients. A potential solution is to use virtual agents that perform motivational interviews. These agents can be rule-based, requiring expert knowledge, or data-driven, needing large datasets for training, which are often hard to obtain. Patient simulation can generate synthetic data as an alternative. Traditionally, this involved template utterances with a dialog manager or uncontrollable black box large language models LLMs. This study proposes a hybrid approach, leveraging both methods to see if LLMs can follow instructed dialog acts while generating natural, coherent utterances. Our study shows that the language model adheres to given conditions and that conditioning on dialog improves the naturalness and coherence of generated utterances, validating our approach for simulating patient responses.
dc.language.isoENen_US
dc.subject.enComputing methodologies
dc.subject.enModeling and simulation
dc.subject.enSimulation evaluation
dc.subject.enHuman-centered computing
dc.subject.enHuman computer interaction (HCI)
dc.subject.enHCI design and evaluation methods
dc.subject.enUser studies
dc.titleSimulating Patient Oral Dialogues: A Study on Naturalness and Coherence of Conditioned Large Language Models
dc.typeCommunication dans un congrèsen_US
dc.identifier.doi10.1145/3652988.3673923en_US
dc.subject.halSciences cognitivesen_US
bordeaux.page1-4en_US
bordeaux.hal.laboratoriesSANPSY (Sommeil, Addiction, Neuropsychiatrie) - UMR 6033en_US
bordeaux.institutionUniversité de Bordeauxen_US
bordeaux.institutionCNRSen_US
bordeaux.conference.titleProceedings of the ACM International Conference on Intelligent Virtual Agentsen_US
bordeaux.countrygben_US
bordeaux.conference.cityGlasgowen_US
bordeaux.import.sourcecrossref
hal.identifierhal-04872527
hal.version1
hal.date.transferred2025-01-08T07:40:50Z
hal.proceedingsouien_US
hal.conference.end2024-09-19
hal.popularnonen_US
hal.audienceInternationaleen_US
hal.exporttrue
workflow.import.sourcecrossref
dc.rights.ccPas de Licence CCen_US
bordeaux.COinSctx_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.title=Simulating%20Patient%20Oral%20Dialogues:%20A%20Study%20on%20Naturalness%20and%20Coherence%20of%20Conditioned%20Large%20Language%20Models&rft.atitle=Simulating%20Patient%20Oral%20Dialogues:%20A%20Study%20on%20Naturalness%20and%20Coherence%20of%20Conditioned%20Large%20Language%20Models&rft.date=2024-12-26&rft.spage=1-4&rft.epage=1-4&rft.au=GALLAND,%20Lucie&PELACHAUD,%20Catherine&PECUNE,%20Florian&rft.genre=unknown


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