2024/09/09 by Жипенг Ли, Xiaofen Xing, Li, Zhipeng +11
Computer Science · #Audio and Speech Processing (eess.AS) #FOS: Electrical engineering #Natural Language Processing Techniques #Speech Recognition and Synthesis #Speech and dialogue systems #electronic engineering #information engineering
paper · pdf · doi:10.48550/arxiv.2409.05730
openalex publication_date 2024/09/09 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
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.