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Conference papers

BAREM: A multimodal dataset of individuals interacting with an e-service platform

Abstract : The use of e-service platforms has become essential for many applications (administrative documents, online shopping, reservations). Although these platforms have improved significantly the user experience, unexpected and stressful situations can occur. Navigation problems (latency, missing information, poor ergonomics) are not always reported to the designers. To address this problem, we propose a multimodal dataset (video, audio, and physiological data) to help implicitly quantify the impact of navigation problems on users when using an e-service platform. A scenario has been designed to generate various navigation problems which can lead to changes in user behaviour. A baseline is proposed to spot changes in user behaviour, opening the way towards automatically qualifying user experiences while using e-service platforms.
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Conference papers
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Contributor : Ioan Marius Bilasco Connect in order to contact the contributor
Submitted on : Thursday, June 17, 2021 - 4:59:22 PM
Last modification on : Tuesday, January 4, 2022 - 6:51:13 AM
Long-term archiving on: : Saturday, September 18, 2021 - 6:54:03 PM


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  • HAL Id : hal-03263944, version 1


Romain Belmonte, Amel Aissaoui, Sofiane Mihoubi, Benjamin Allaert, José Mennesson, et al.. BAREM: A multimodal dataset of individuals interacting with an e-service platform. CBMI 2021 - Content-based Multimedia Indexing, Jun 2021, Lille / Virtual, France. ⟨hal-03263944⟩



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