SocialNLP EmotionX 2019 Challenge Overview: Predicting Emotions in Spoken Dialogues and Chats

September 17, 2019 ยท Declared Dead ยท ๐Ÿ› arXiv.org

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Authors Boaz Shmueli, Lun-Wei Ku arXiv ID 1909.07734 Category cs.CL: Computation & Language Citations 26 Venue arXiv.org Last Checked 4 months ago
Abstract
We present an overview of the EmotionX 2019 Challenge, held at the 7th International Workshop on Natural Language Processing for Social Media (SocialNLP), in conjunction with IJCAI 2019. The challenge entailed predicting emotions in spoken and chat-based dialogues using augmented EmotionLines datasets. EmotionLines contains two distinct datasets: the first includes excerpts from a US-based TV sitcom episode scripts (Friends) and the second contains online chats (EmotionPush). A total of thirty-six teams registered to participate in the challenge. Eleven of the teams successfully submitted their predictions performance evaluation. The top-scoring team achieved a micro-F1 score of 81.5% for the spoken-based dialogues (Friends) and 79.5% for the chat-based dialogues (EmotionPush).
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