@inproceedings{pan-etal-2024-umuteam-semeval-2024-task,
title = "{UMUT}eam at {S}em{E}val-2024 Task 10: Discovering and Reasoning about Emotions in Conversation using Transformers",
author = "Pan, Ronghao and
Garc{\'\i}a-d{\'\i}az, Jos{\'e} Antonio and
Rold{\'a}n, Diego and
Valencia-garc{\'\i}a, Rafael",
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-1.101",
doi = "10.18653/v1/2024.semeval-1.101",
pages = "703--709",
abstract = "These notes describe the participation of the UMUTeam in EDiReF, the 10th shared task of SemEval 2024. The goal is to develop systems for detecting and inferring emotional changes in the conversation. The task was divided into three related subtasks: (i) Emotion Recognition in Conversation (ERC) in Hindi-English code-mixed conversations, (ii) Emotion Flip Reasoning (EFR) in Hindi-English code-mixed conversations, and (iii) EFR in English conversations. We were involved in all three and our approach is based on a fine-tuning approach with different pre-trained models. After evaluation, we found BERT to be the best model for ERC and EFR and with this model we achieved the thirteenth best result with an F1 score of 43{\%} in Subtask 1, the sixth best in Subtask 2 with an F1 score of 26{\%} and the fifteenth best in Subtask 3 with an F1 score of 22{\%}.",
}
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<abstract>These notes describe the participation of the UMUTeam in EDiReF, the 10th shared task of SemEval 2024. The goal is to develop systems for detecting and inferring emotional changes in the conversation. The task was divided into three related subtasks: (i) Emotion Recognition in Conversation (ERC) in Hindi-English code-mixed conversations, (ii) Emotion Flip Reasoning (EFR) in Hindi-English code-mixed conversations, and (iii) EFR in English conversations. We were involved in all three and our approach is based on a fine-tuning approach with different pre-trained models. After evaluation, we found BERT to be the best model for ERC and EFR and with this model we achieved the thirteenth best result with an F1 score of 43% in Subtask 1, the sixth best in Subtask 2 with an F1 score of 26% and the fifteenth best in Subtask 3 with an F1 score of 22%.</abstract>
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%0 Conference Proceedings
%T UMUTeam at SemEval-2024 Task 10: Discovering and Reasoning about Emotions in Conversation using Transformers
%A Pan, Ronghao
%A García-díaz, José Antonio
%A Roldán, Diego
%A Valencia-garcía, Rafael
%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 pan-etal-2024-umuteam-semeval-2024-task
%X These notes describe the participation of the UMUTeam in EDiReF, the 10th shared task of SemEval 2024. The goal is to develop systems for detecting and inferring emotional changes in the conversation. The task was divided into three related subtasks: (i) Emotion Recognition in Conversation (ERC) in Hindi-English code-mixed conversations, (ii) Emotion Flip Reasoning (EFR) in Hindi-English code-mixed conversations, and (iii) EFR in English conversations. We were involved in all three and our approach is based on a fine-tuning approach with different pre-trained models. After evaluation, we found BERT to be the best model for ERC and EFR and with this model we achieved the thirteenth best result with an F1 score of 43% in Subtask 1, the sixth best in Subtask 2 with an F1 score of 26% and the fifteenth best in Subtask 3 with an F1 score of 22%.
%R 10.18653/v1/2024.semeval-1.101
%U https://aclanthology.org/2024.semeval-1.101
%U https://doi.org/10.18653/v1/2024.semeval-1.101
%P 703-709
Markdown (Informal)
[UMUTeam at SemEval-2024 Task 10: Discovering and Reasoning about Emotions in Conversation using Transformers](https://aclanthology.org/2024.semeval-1.101) (Pan et al., SemEval 2024)
ACL