An end-to-end LLM system that jointly predicts transcripts, emotion descriptors, and emotion labels from speech, with VAE-based disentanglement, beats its own multi-task baselines on IEMOCAP and MELD.
Alternating Multi-task Fine-tuning A parameter-efficient fine-tuning method known as low-rank adaptation, or LoRA [27], is widely employed to fine-tune the LLM-based models
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Towards LLM-Empowered Fine-Grained Speech Descriptors for Explainable Emotion Recognition
An end-to-end LLM system that jointly predicts transcripts, emotion descriptors, and emotion labels from speech, with VAE-based disentanglement, beats its own multi-task baselines on IEMOCAP and MELD.