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There has been significant progress in emotional Text-To-Speech (TTS)synthesis technology in recent years. However, existing methods primarily focuson the synthesis of a limited number of emotion types and have achievedunsatisfactory performance in intensity control. To address these limitations,we propose EmoMix, which can generate emotional speech with specified intensityor a mixture of emotions. Specifically, EmoMix is a controllable emotional TTSmodel based on a diffusion probabilistic model and a pre-trained speech emotionrecognition (SER) model used to extract emotion embedding. Mixed emotionsynthesis is achieved by combining the noises predicted by diffusion modelconditioned on different emotions during only one sampling process at therun-time. We further apply the Neutral and specific primary emotion mixed invarying degrees to control intensity. Experimental results validate theeffectiveness of EmoMix for synthesizing mixed emotion and intensity control.

EmoMix: Emotion Mixing via Diffusion Models for Emotional Speech Synthesis