Exploring Emotion Expression Recognition in Older Adults Interacting With a Virtual Coach
The EMPATHIC project aimed to design an emotionally expressive virtual coach capable of engaging healthy seniors to improve well-being and promote independent aging. In particular, the system's human sensing capabilities allow for the perception of emotional states to provide a personalized experience. This paper outlines the development of the emotion expression recognition module of the virtual coach, encompassing data collection, annotation design, and a first methodological approach, all tailored to the project requirements. With the latter, we investigate the role of various modalities, individually and combined, for discrete emotion expression recognition in this context: speech from audio, and facial expressions, gaze, and head dynamics from video. The collected corpus includes users from Spain, France, and Norway, and was annotated separately for the audio and video channels with distinct emotional labels, allowing for a performance comparison across cultures and label types. Results confirm the informative power of the modalities studied for the emotional categories considered, with multimodal methods generally outperforming others (around 68% accuracy with audio labels and 72-74% with video labels). The findings are expected to contribute to the limited literature on emotion recognition applied to older adults in conversational human-machine interaction, and guide the development of future systems.
Authors
- Maria Stylianou Korsnes (ORCID: https://orcid.org/0000-0003-0774-5147)
- Anna Esposito (ORCID: https://orcid.org/0000-0002-7268-1795)
- Dijana Petrovska‐Delacrétaz (ORCID: https://orcid.org/0000-0001-6485-2972)
- Leila Ben Letaifa
- Anna Torp Johansen
- Mohamed Amine Hmani (ORCID: https://orcid.org/0000-0002-2403-2643)
- Pau Buch-Cardona
- Terry Amorese (ORCID: https://orcid.org/0000-0002-9987-2823)
- Sérgio Escalera (ORCID: https://orcid.org/0000-0003-0617-8873)
- Mounîm A. El‐Yacoubi (ORCID: https://orcid.org/0000-0002-7383-0588)
- Mikel deVelasco (ORCID: https://orcid.org/0000-0002-6131-712X)
- M. Inés Torres (ORCID: https://orcid.org/0000-0002-1773-3214)
- Eduardo González–Fraile (ORCID: https://orcid.org/0000-0001-9381-3358)
- Cristina Palmero (ORCID: https://orcid.org/0000-0002-6085-6527)
- Micaela Rodrigues da Silva
- Aymen Mtibaa
- Gennaro Cordasco (ORCID: https://orcid.org/0000-0001-9148-9769)
- Raquel Justo (ORCID: https://orcid.org/0000-0002-3142-539X)
- Liva J. Martinussen (ORCID: https://orcid.org/0000-0002-0111-8970)
- Jofre Tenorio‐Laranga
- B. Fernández-Ruanova
Institutions
- Oslo University Hospital (NO)
- University of the Basque Country (ES)
- University of Campania "Luigi Vanvitelli" (IT)
- Barcelona Supercomputing Center (ES)
- Universidad Internacional De La Rioja (ES)
- University of Campania "Luigi Vanvitelli" (IT)
- Azienda Ospedaliera Universitaria Università degli Studi della Campania Luigi Vanvitelli (IT)
- Institut Polytechnique de Paris (FR)
- Computer Vision Center
- Universitat de Barcelona (ES)
Publication Details
- Journal
- IEEE Transactions on Affective Computing
- Published
- 2025-04-08
- DOI
- https://doi.org/10.1109/taffc.2025.3558141
- Citations
- 3
- Primary Topic
- Emotional Intelligence and Performance
- Type
- article
- Field-Weighted Citation Impact
- 7.32