SubmissionNumber#=%=#186
FinalPaperTitle#=%=#MorphingMinds at SemEval-2024 Task 10: Emotion Recognition in Conversation in Hindi-English Code-Mixed Conversations
ShortPaperTitle#=%=#
NumberOfPages#=%=#5
CopyrightSigned#=%=#Monika Vyas
JobTitle#==#
Organization#==#Monika Vyas and Purdue University Fort Wayne
Abstract#==#The research focuses on emotion detection in multilingual conversations, particularly in Romanized Hindi and English, with applications in sentiment analysis and mental health assessments. The study employs Machine learning, deep learning techniques, including Transformer-based models like XLM-RoBERTa, for feature extraction and emotion classification. Various experiments are conducted to evaluate model performance, including fine-tuning, data augmentation, and addressing dataset imbalances. The findings highlight challenges and opportunities in emotion detection across languages and emphasize culturally sensitive approaches. The study contributes to advancing emotion analysis in multilingual contexts and provides practical guidance for developing more accurate emotion detection systems.
Author{1}{Firstname}#=%=#Monika
Author{1}{Lastname}#=%=#Vyas
Author{1}{Username}#=%=#vyasm01
Author{1}{Email}#=%=#vyasm01@pfw.edu
Author{1}{Affiliation}#=%=#Purdue University Fort wayne

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