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.

Dans cet article, nous proposons des approches pour améliorer les architectures basées sur des transformeurs pour la classification de documents multi-labels. Les dépendances entre les labels sont cruciales dans ce contexte. Notre méthode, appelée DepReg, ajoute un terme de régularisation à la fonction de perte pour encourager le modèle à prédire des labels susceptibles de coexister. Nous introduisons également un nouveau jeu de données nommé “arXiv-ACM”, composé de résumés scientifiques de la bibliothèque numérique arXiv, étiquetés avec les mots-clés ACM correspondants.

This paper focuses on the representation and querying of knowledge-based multimodal data. This work stands in the OTIM project which aims at processing multimodal annotation of a large conversational French speech corpus. Within OTIM, we aim at providing linguists with a unique framework to encode and manipulate numerous linguistic domains (from prosody to gesture). Linguists commonly use Typed Feature Structures (TFS) to provide an uniform view of multimodal annotations but such a representation cannot be used within an applicative framework. Moreover TFS expressibility is limited to hierarchical and constituency relations and does not suit to any linguistic domain that needs for example to represent temporal relations. To overcome these limits, we propose an ontological approach based on Description logics (DL) for the description of linguistic knowledge and we provide an applicative framework based on OWL DL (Ontology Web Language) and the query language SPARQL.