Abstract
In recent years, emotional Text-to-Speech (TTS) synthesis and emphasis-controllable speech synthesis have advanced significantly. However, their interaction remains underexplored. We propose Emphasis Meets Emotion TTS (EME-TTS), a novel framework designed to address two key research questions: (1) how to effectively utilize emphasis to enhance the expressiveness of emotional speech, and (2) how to maintain the perceptual clarity and stability of target emphasis across different emotions. EME-TTS employs weakly supervised learning with emphasis pseudo-labels and variance-based emphasis features. Additionally, the proposed Emphasis Perception Enhancement (EPE) block enhances the interaction between emotional signals and emphasis positions. Experimental results show that EME-TTS, when combined with large language models for emphasis position prediction, enables more natural emotional speech synthesis while preserving stable and distinguishable target emphasis across emotions. Synthesized samples are available on-line.
Abstract (translated)
近年来，情感文本到语音（TTS）合成和可控制重音的语音合成技术取得了显著进展。然而，这两者的相互作用尚未得到充分研究。我们提出了一种名为“Emphasis Meets Emotion TTS”（EME-TTS）的新框架，旨在解决以下两个关键研究问题：(1) 如何有效地利用重音来增强情感语音的表现力；(2) 如何在不同情绪下保持目标重音的感知清晰度和稳定性。EME-TTS采用带有弱监督学习和基于方差的重音伪标签以及重音特征的方法，并提出了增强情感信号与重音位置之间互动的“Emphasis Perception Enhancement”（EPE）模块。实验结果显示，当结合大型语言模型进行重音位置预测时，EME-TTS能够生成更加自然的情感语音合成结果，同时在不同情绪下保持稳定且可区分的目标重音。合成样本可在在线平台上获取。
URL
https://arxiv.org/abs/2507.12015
