Emo-LiPO applies listwise preference optimization to model global emotion intensity ordering in LLM TTS, yielding better accuracy and controllability than supervised or DPO baselines on a new multi-speaker dataset.
Emosphere-tts: Emo- tional style and intensity modeling via spherical emotion vec- tor for controllable emotional text-to-speech
2 Pith papers cite this work. Polarity classification is still indexing.
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Pith papers citing it
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An emotion TTS system adjusts Classifier-Free Guidance strength according to text-style semantic mismatch; it shows small emotion-accuracy gains, but headline baselines and subjective results are absent from the main text.
citing papers explorer
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Emo-LiPO: Listwise Preference Optimization for Fine-Grained Emotion Intensity Control in LLM-based Text-to-Speech
Emo-LiPO applies listwise preference optimization to model global emotion intensity ordering in LLM TTS, yielding better accuracy and controllability than supervised or DPO baselines on a new multi-speaker dataset.
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Cross-modal Consistency Guidance for Robust Emotion Control in Auto-Regressive TTS Models
An emotion TTS system adjusts Classifier-Free Guidance strength according to text-style semantic mismatch; it shows small emotion-accuracy gains, but headline baselines and subjective results are absent from the main text.