Exploring Emotion Expression Recognition in Older Adults Interacting with a Virtual Coach
Abstract
The EMPATHIC project aimed to design an emotionally expressive virtual coach capable of engaging healthy seniors to improve well-being and promote independent aging. One of the core aspects of the system is its human sensing capabilities, allowing 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.
Cite
@article{arxiv.2311.05567,
title = {Exploring Emotion Expression Recognition in Older Adults Interacting with a Virtual Coach},
author = {Cristina Palmero and Mikel deVelasco and Mohamed Amine Hmani and Aymen Mtibaa and Leila Ben Letaifa and Pau Buch-Cardona and Raquel Justo and Terry Amorese and Eduardo González-Fraile and Begoña Fernández-Ruanova and Jofre Tenorio-Laranga and Anna Torp Johansen and Micaela Rodrigues da Silva and Liva Jenny Martinussen and Maria Stylianou Korsnes and Gennaro Cordasco and Anna Esposito and Mounim A. El-Yacoubi and Dijana Petrovska-Delacrétaz and M. Inés Torres and Sergio Escalera},
journal= {arXiv preprint arXiv:2311.05567},
year = {2024}
}
Comments
This work has been submitted to the IEEE for possible publication