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Autori principali: Li, Zhipeng, Xing, Xiaofen, Wang, Jun, Chen, Shuaiqi, Yu, Guoqiao, Wan, Guanglu, Xu, Xiangmin
Natura: Preprint
Pubblicazione: 2024
Soggetti:
Accesso online:https://arxiv.org/abs/2409.05730
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Sommario:
  • In recent years, there has been significant progress in Text-to-Speech (TTS) synthesis technology, enabling the high-quality synthesis of voices in common scenarios. In unseen situations, adaptive TTS requires a strong generalization capability to speaker style characteristics. However, the existing adaptive methods can only extract and integrate coarse-grained timbre or mixed rhythm attributes separately. In this paper, we propose AS-Speech, an adaptive style methodology that integrates the speaker timbre characteristics and rhythmic attributes into a unified framework for text-to-speech synthesis. Specifically, AS-Speech can accurately simulate style characteristics through fine-grained text-based timbre features and global rhythm information, and achieve high-fidelity speech synthesis through the diffusion model. Experiments show that the proposed model produces voices with higher naturalness and similarity in terms of timbre and rhythm compared to a series of adaptive TTS models.