Abstract
Chatbots allow computer programs to interact naturally with a user. However, they remain limited due to their lack of sensitivity to the user’s state of mind and emotions. This sensitivity will allow the chatbots to provide more accurate answers. Text-based emotion detection has already been explored for the english language (Chatterjee et al., 2019), yet no satisfying french dataset is available. We propose to translate the emotion corpus of multi-party conversation EmotionLines, which is based on the Friends TV show, by exploiting its french broadcasting. Our translation-based dataset generation method is adaptable to any dataset deriving from foreign movies, or TV shows broadcasted in french. Using this translated dataset, we propose a classifier based on BERT, able to detect the user’s emotion from text. It takes into account the context of the discussion to improve its inferences.
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