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2018-07-20 - Colloque/Article dans les actes avec comité de lecture - Anglais - 5 page(s)

Tits Noé , El Haddad Kevin , Dutoit Thierry , "ASR-based Features for Emotion Recognition: A Transfer Learning Approach" in Grand Challenge and Workshop on Human Multimodal Language, Melbourne, Australia, 2018

  • Codes CREF : Intelligence artificielle (DI1180), Technologies de l'information et de la communication (TIC) (DI4730)
  • Unités de recherche UMONS : Théorie des circuits et Traitement du signal (F105)
  • Instituts UMONS : Institut NUMEDIART pour les Technologies des Arts Numériques (Numédiart)
Texte intégral :

Abstract(s) :

(Anglais) In this paper, we investigate the use of a neural Automatic Speech Recognition (ASR) as a feature extractor for emotion recognition. We show that these features outperform the eGeMAPS feature set to predict the valence and arousal emotional dimensions, which means that the audio-to-text mapping learned by the ASR system contains information related to the emotional dimensions in spontaneous speech. We also examine the relationship between first layers (closer to speech) and last layers (closer to text) of the ASR and valence/arousal.