5 papers
Follow the Clues, Frame the Truth: Hybrid-evidential Deductive Reasoning in Open-Vocabulary Multimodal Emotion Recognition
Yu Liu, Lei Zhang, Haoxun Li +4
Open-Vocabulary Multimodal Emotion Recognition (OV-MER) is inherently challenging due to the ambiguity of equivocal multimodal cues, which often stem from distinct unobserved situa…
EMORL-TTS: Reinforcement Learning for Fine-Grained Emotion Control in LLM-based TTS
Haoxun Li, Yu Liu, Yuqing Sun +3
Recent LLM-based TTS systems achieve strong quality and zero-shot ability, but lack fine-grained emotional control due to their reliance on discrete speech tokens. Existing approac…
MSF-SER: Enriching Acoustic Modeling with Multi-Granularity Semantics for Speech Emotion Recognition
Haoxun Li, Yuqing Sun, Hanlei Shi +3
Continuous dimensional speech emotion recognition captures affective variation along valence, arousal, and dominance, providing finer-grained representations than categorical appro…
Centering Emotion Hotspots: Multimodal Local-Global Fusion and Cross-Modal Alignment for Emotion Recognition in Conversations
Yu Liu, Hanlei Shi, Haoxun Li +5
Emotion Recognition in Conversations (ERC) is hard because discriminative evidence is sparse, localized, and often asynchronous across modalities. We center ERC on emotion hotspots…
EME-TTS: Unlocking the Emphasis and Emotion Link in Speech Synthesis
Haoxun Li, Leyuan Qu, Jiaxi Hu +1
In recent years, emotional Text-to-Speech (TTS) synthesis and emphasis-controllable speech synthesis have advanced significantly. However, their interaction remains underexplored.…