Artículos de revistas
Emotion Recognition in Never-Seen Languages Using a Novel Ensemble Method With Emotion Profiles
Fecha
2017-01Registro en:
Albornoz, Enrique Marcelo; Milone, Diego Humberto; Emotion Recognition in Never-Seen Languages Using a Novel Ensemble Method With Emotion Profiles; IEEE; IEEE Transactions on Affective Computing; 8; 1-2017; 43-53
1949-3045
CONICET Digital
CONICET
Autor
Albornoz, Enrique Marcelo
Milone, Diego Humberto
Resumen
Over the last years, researchers have addressed emotional state identification because it is an important issue to achieve more natural speech interactive systems. There are several theories that explain emotional expressiveness as a result of natural evolution, as a social construction, or a combination of both. In this work, we propose a novel system to model each language independently, preserving the cultural properties. In a second stage, we use the concept of universality of emotions to map and predict emotions in never-seen languages. Features and classifiers widely tested for similar tasks were used to set the baselines. We developed a novel ensemble classifier to deal with multiple languages and tested it on never-seen languages. Furthermore, this ensemble uses the Emotion Profiles technique in order to map features from diverse languages in a more tractable space. The experiments were performed in a language-independent scheme. Results show that the proposed model improves the baseline accuracy, whereas its modular design allows the incorporation of a new language without having to train the whole system.