SSR-Speech: Towards Stable, Safe and Robust Zero-shot Text-based Speech Editing and Synthesis

Fuente: arXiv
Enregistré dans:
Détails bibliographiques
Auteurs principaux: Wang, Helin, Yu, Meng, Hai, Jiarui, Chen, Chen, Hu, Yuchen, Chen, Rilin, Dehak, Najim, Yu, Dong
Format: Preprint
Publié: 2024
Sujets:
Accès en ligne:
Tags: Ajouter un tag
Pas de tags, Soyez le premier à ajouter un tag!
_version_ 1866912174124826624
author Wang, Helin
Yu, Meng
Hai, Jiarui
Chen, Chen
Hu, Yuchen
Chen, Rilin
Dehak, Najim
Yu, Dong
author_facet Wang, Helin
Yu, Meng
Hai, Jiarui
Chen, Chen
Hu, Yuchen
Chen, Rilin
Dehak, Najim
Yu, Dong
contents In this paper, we introduce SSR-Speech, a neural codec autoregressive model designed for stable, safe, and robust zero-shot textbased speech editing and text-to-speech synthesis. SSR-Speech is built on a Transformer decoder and incorporates classifier-free guidance to enhance the stability of the generation process. A watermark Encodec is proposed to embed frame-level watermarks into the edited regions of the speech so that which parts were edited can be detected. In addition, the waveform reconstruction leverages the original unedited speech segments, providing superior recovery compared to the Encodec model. Our approach achieves state-of-the-art performance in the RealEdit speech editing task and the LibriTTS text-to-speech task, surpassing previous methods. Furthermore, SSR-Speech excels in multi-span speech editing and also demonstrates remarkable robustness to background sounds. The source code and demos are released.
format Preprint
id arxiv_https___arxiv_org_abs_2409_07556
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle SSR-Speech: Towards Stable, Safe and Robust Zero-shot Text-based Speech Editing and Synthesis
Wang, Helin
Yu, Meng
Hai, Jiarui
Chen, Chen
Hu, Yuchen
Chen, Rilin
Dehak, Najim
Yu, Dong
Audio and Speech Processing
Sound
In this paper, we introduce SSR-Speech, a neural codec autoregressive model designed for stable, safe, and robust zero-shot textbased speech editing and text-to-speech synthesis. SSR-Speech is built on a Transformer decoder and incorporates classifier-free guidance to enhance the stability of the generation process. A watermark Encodec is proposed to embed frame-level watermarks into the edited regions of the speech so that which parts were edited can be detected. In addition, the waveform reconstruction leverages the original unedited speech segments, providing superior recovery compared to the Encodec model. Our approach achieves state-of-the-art performance in the RealEdit speech editing task and the LibriTTS text-to-speech task, surpassing previous methods. Furthermore, SSR-Speech excels in multi-span speech editing and also demonstrates remarkable robustness to background sounds. The source code and demos are released.
title SSR-Speech: Towards Stable, Safe and Robust Zero-shot Text-based Speech Editing and Synthesis
topic Audio and Speech Processing
Sound
url https://arxiv.org/abs/2409.07556