Supriya Abirami A

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2024

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SSN_Semeval10 at SemEval-2024 Task 10: Emotion Discovery and Reasoning its Flip in Conversations
Antony Rajesh A | Supriya Abirami A | Chandrabose Aravindan | Senthil Kumar B
Proceedings of the 18th International Workshop on Semantic Evaluation (SemEval-2024)

This paper presents a transformer-based model for recognizing emotions in Hindi-English code-mixed conversations, adhering to the SemEval task constraints. Leveraging BERT-based transformers, we fine-tune pre-trained models on the dataset, incorporating tokenization and attention mechanisms. Our approach achieves competitive performance (weighted F1-score of 0.4), showcasing the effectiveness of BERT in nuanced emotion analysis tasks within code-mixed conversational contexts.
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