HingRoBERTa ERC — E-MASAC

Fine-tuned l3cube-pune/hing-roberta for Emotion Recognition in Conversation (ERC) on the SemEval-2024 Task 10 E-MASAC benchmark (Hinglish TV dialogues from Sarabhai vs. Sarabhai).

Performance

Test wF1: 0.4852 (HingRoBERTa + SVM soft ensemble)
Phase 1 alone: wF1 = 0.3901
+12.5 pts above SemEval LSTM baseline

Architecture

Two-phase ensemble:

Phase 1: Fine-tuned HingRoBERTa with Focal Loss + R-Drop, speaker embeddings, emotion-conditioned context
Phase 2: SVM-RBF on 3,185-d features (Phase 1 embeddings + hand-crafted conversational features)

Labels

anger, contempt, disgust, fear, joy, neutral, sadness, surprise

Citation

Chakradhar Kotha, Konda Bhanu Sai Akhil, Venkata Siva Sai Krishna Pokuri IIIT Hyderabad | SemEval-2024 Task 10

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