用扩散模型分层建模语音韵律，实现多样可控的语音合成。
DiffStyleTTS: Diffusion-based Hierarchical Prosody Modeling for Text-to-Speech with Diverse and Controllable Styles
- 基于条件扩散模块分层建模语音韵律特征
- 自然度优于所有基线，合成速度更快
- 通过调节引导强度灵活控制语音风格
人类语音具有丰富多变的韵律特征。为合理且灵活地解决文本到韵律的一对多映射问题，我们提出DiffStyleTTS，一种基于条件扩散模块和改进无分类器引导的多说话人声学模型，该模型分层建模语音韵律特征，并通过控制不同韵律风格来指导韵律预测。实验表明，该方法在自然度上优于所有基线，合成速度也快于三种扩散基线。此外，通过调整引导尺度，可有效控制合成韵律的引导强度。
原文摘要 · Abstract (English)
Human speech exhibits rich and flexible prosodic variations. To address the one-to-many mapping problem from text to prosody in a reasonable and flexible manner, we propose DiffStyleTTS, a multi-speaker acoustic model based on a conditional diffusion module and an improved classifier-free guidance, which hierarchically models speech prosodic features, and controls different prosodic styles to guide prosody prediction. Experiments show that our method outperforms all baselines in naturalness and achieves superior synthesis speed compared to three diffusion-based baselines. Additionally, by adjusting the guiding scale, DiffStyleTTS effectively controls the guidance intensity of the synthetic prosody.
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