arXiv AI
ER-EDF: A Psychology-Grounded Emotion Regulation Framework for Speech Empathetic Dialogue Generation in Large Audio-Language Models
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EmoStance: Response-Side Affective-Orientation Control for Empathetic Response Generation via Emoji Weak Supervision
The paper introduces EmoStance, a method for controlling the affective orientation of empathetic responses by leveraging weak supervision from emoji distributions. It builds the EmojiDialogue dataset, extending EmpatheticDialogues with emoji votes and confidence scores, and uses a frozen instruction‑tuned LLM steered by continuous prefix embeddings to generate responses that align with the listener’s stance. In blind pairwise evaluations, EmoStance achieves a 62.2% decisive win rate, notably improving contextual specificity and perceived responsiveness compared to baselines.
Hugging Face Trending Papers
Sep 2
EmoStance: Response-Side Affective-Orientation Control for Empathetic Response Generation via Emoji Weak Supervision
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arXiv AI
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Self-EmoQ: Plutchik-Guided Value-based Planning to Drive Streaming Emotional TTS
arXiv:2606. 09837v1 Announce Type: cross Abstract: Emotional interaction is increasingly crucial for conversational AI, yet current systems lack a self-emotion determination mechanism to drive the streaming text-to-speech (TTS) synthesis.