EMOLIS App and Dataset to Find Emotionally Close Cartoons
Soëlie Lerch, Patrice Bellot, Elisabeth Murisasco, Emmanuel Bruno
Abstract
We propose EMOLIS Dataset that contains annotated emotional transcripts of scenes from Walt Disney cartoons at the same time as physiological signals from spectators (breathing, ECG, eye movements). The dataset is used in EMOLIS App, our second proposal. EMOLIS App allows to display the identified emotions while a video is playing and suggest emotionally comparable videos. We propose to estimate an emotional distance between videos using multimodal neural representations (text, audio, video) that also combine physiological signals. This enables personalized results that can be used for cognitive therapies focusing on awareness of felt emotions. The dataset is designed to be suitable for all audiences and autistic people who have difficulties to recognize and express emotions.- Anthology ID:
- 2024.lrec-main.502
- Volume:
- Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024)
- Month:
- May
- Year:
- 2024
- Address:
- Torino, Italia
- Editors:
- Nicoletta Calzolari, Min-Yen Kan, Veronique Hoste, Alessandro Lenci, Sakriani Sakti, Nianwen Xue
- Venues:
- LREC | COLING
- SIG:
- Publisher:
- ELRA and ICCL
- Note:
- Pages:
- 5654–5659
- Language:
- URL:
- https://aclanthology.org/2024.lrec-main.502
- DOI:
- Cite (ACL):
- Soëlie Lerch, Patrice Bellot, Elisabeth Murisasco, and Emmanuel Bruno. 2024. EMOLIS App and Dataset to Find Emotionally Close Cartoons. In Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024), pages 5654–5659, Torino, Italia. ELRA and ICCL.
- Cite (Informal):
- EMOLIS App and Dataset to Find Emotionally Close Cartoons (Lerch et al., LREC-COLING 2024)
- PDF:
- https://preview.aclanthology.org/nschneid-patch-4/2024.lrec-main.502.pdf