Emotional Speech Synthesis
Overview
Emotional speech synthesis studies how to make generated speech convey feelings, intensity, and changing affect while keeping the words clear and the voice consistent. Systems use emotion labels or natural-language instructions, prosody controls such as pitch and duration, and newer autoregressive, diffusion, and flow-matching models; preference learning and activation steering offer ways to refine control. Some work also uses dialogue context or visual cues to plan an emotionally appropriate response. A central challenge is balancing expressive, fine-grained control with naturalness, intelligibility, and speaker identity, while ensuring automatic emotion measures reflect human judgments.
Latest papers
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