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Recognizing Emotion Cause in Conversations


We address the problem of recognizing emotion cause in conversations, define two novel sub-tasks of this problem, and provide a corresponding dialogue-level dataset, along with strong transformer-based baselines. The dataset is available at Recognizing the cause behind emotions in text is a fundamental yet under-explored area of research in NLP. Advances in this area hold the potential to improve interpretability and performance in affect-based models. Identifying emotion causes at the utterance level in conversations is particularly challenging due to the intermingling dynamics among the interlocutors. We introduce the task of Recognizing Emotion Cause in CONversations with an accompanying dataset named RECCON, containing over 1,000 dialogues and 10,000 utterance cause/effect pairs. Furthermore, we define different cause types based on the source of the causes, and establish strong Transformer-based baselines to address two different sub-tasks on this dataset. Our transformer-based baselines, which leverage contextual pre-trained embeddings, such as RoBERTa, outperform the state-of-the-art emotion cause extraction approaches on our dataset. We introduce a new task highly relevant for (explainable) emotion-aware artificial intelligence: recognizing emotion cause in conversations, provide a new highly challenging publicly available dialogue-level dataset for this task, and give strong baseline results on this dataset.

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  1. pronounced as reckon.

  2. By “causal span from evidence in the context” we mean a causal span from the conversation history \(H(U_t)\).


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Correspondence to Alexander Gelbukh.

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Additional information

S. Poria, N. Majumder, D. Ghosal, R. Bhardwaj, S. Yu Bai Jian, and P. Hong have received support from the A*STAR under its RIE 2020 Advanced Manufacturing and Engineering programmatic grant, Award No. A19E2b0098. A. Gelbukh has received support from the Mexican Government through the grant A1-S-47854 of the CONACYT, Mexico, and grants 20211784, 20211884, and 20211178 of the Secretaría de Investigación y Posgrado of the Instituto Politécnico Nacional, Mexico.

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Poria, S., Majumder, N., Hazarika, D. et al. Recognizing Emotion Cause in Conversations. Cogn Comput 13, 1317–1332 (2021).

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