@inproceedings{kumar-etal-2024-semeval,
title = "{S}em{E}val 2024 - Task 10: Emotion Discovery and Reasoning its Flip in Conversation ({ED}i{R}e{F})",
author = "Kumar, Shivani and
Akhtar, Md. Shad and
Cambria, Erik and
Chakraborty, Tanmoy",
editor = {Ojha, Atul Kr. and
Do{\u{g}}ru{\"o}z, A. Seza and
Tayyar Madabushi, Harish and
Da San Martino, Giovanni and
Rosenthal, Sara and
Ros{\'a}, Aiala},
booktitle = "Proceedings of the 18th International Workshop on Semantic Evaluation (SemEval-2024)",
month = jun,
year = "2024",
address = "Mexico City, Mexico",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2024.semeval-1.270/",
doi = "10.18653/v1/2024.semeval-1.270",
pages = "1933--1946",
abstract = "We present SemEval-2024 Task 10, a shared task centred on identifying emotions and finding the rationale behind their flips within monolingual English and Hindi-English code-mixed dialogues. This task comprises three distinct subtasks {--} emotion recognition in conversation for code-mixed dialogues, emotion flip reasoning for code-mixed dialogues, and emotion flip reasoning for English dialogues. Participating systems were tasked to automatically execute one or more of these subtasks. The datasets for these tasks comprise manually annotated conversations focusing on emotions and triggers for emotion shifts.1 A total of 84 participants engaged in this task, with the most adept systems attaining F1-scores of 0.70, 0.79, and 0.76 for the respective subtasks. This paper summarises the results and findings from 24 teams alongside their system descriptions."
}
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%0 Conference Proceedings
%T SemEval 2024 - Task 10: Emotion Discovery and Reasoning its Flip in Conversation (EDiReF)
%A Kumar, Shivani
%A Akhtar, Md. Shad
%A Cambria, Erik
%A Chakraborty, Tanmoy
%Y Ojha, Atul Kr.
%Y Doğruöz, A. Seza
%Y Tayyar Madabushi, Harish
%Y Da San Martino, Giovanni
%Y Rosenthal, Sara
%Y Rosá, Aiala
%S Proceedings of the 18th International Workshop on Semantic Evaluation (SemEval-2024)
%D 2024
%8 June
%I Association for Computational Linguistics
%C Mexico City, Mexico
%F kumar-etal-2024-semeval
%X We present SemEval-2024 Task 10, a shared task centred on identifying emotions and finding the rationale behind their flips within monolingual English and Hindi-English code-mixed dialogues. This task comprises three distinct subtasks – emotion recognition in conversation for code-mixed dialogues, emotion flip reasoning for code-mixed dialogues, and emotion flip reasoning for English dialogues. Participating systems were tasked to automatically execute one or more of these subtasks. The datasets for these tasks comprise manually annotated conversations focusing on emotions and triggers for emotion shifts.1 A total of 84 participants engaged in this task, with the most adept systems attaining F1-scores of 0.70, 0.79, and 0.76 for the respective subtasks. This paper summarises the results and findings from 24 teams alongside their system descriptions.
%R 10.18653/v1/2024.semeval-1.270
%U https://aclanthology.org/2024.semeval-1.270/
%U https://doi.org/10.18653/v1/2024.semeval-1.270
%P 1933-1946
Markdown (Informal)
[SemEval 2024 - Task 10: Emotion Discovery and Reasoning its Flip in Conversation (EDiReF)](https://aclanthology.org/2024.semeval-1.270/) (Kumar et al., SemEval 2024)
ACL