FleSpeech: Flexibly Controllable Speech Generation with Various Prompts

Fuente: arXiv
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Auteurs principaux: Li, Hanzhao, Li, Yuke, Wang, Xinsheng, Hu, Jingbin, Xie, Qicong, Yang, Shan, Xie, Lei
Format: Preprint
Publié: 2025
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author Li, Hanzhao
Li, Yuke
Wang, Xinsheng
Hu, Jingbin
Xie, Qicong
Yang, Shan
Xie, Lei
author_facet Li, Hanzhao
Li, Yuke
Wang, Xinsheng
Hu, Jingbin
Xie, Qicong
Yang, Shan
Xie, Lei
contents Controllable speech generation methods typically rely on single or fixed prompts, hindering creativity and flexibility. These limitations make it difficult to meet specific user needs in certain scenarios, such as adjusting the style while preserving a selected speaker's timbre, or choosing a style and generating a voice that matches a character's visual appearance. To overcome these challenges, we propose \textit{FleSpeech}, a novel multi-stage speech generation framework that allows for more flexible manipulation of speech attributes by integrating various forms of control. FleSpeech employs a multimodal prompt encoder that processes and unifies different text, audio, and visual prompts into a cohesive representation. This approach enhances the adaptability of speech synthesis and supports creative and precise control over the generated speech. Additionally, we develop a data collection pipeline for multimodal datasets to facilitate further research and applications in this field. Comprehensive subjective and objective experiments demonstrate the effectiveness of FleSpeech. Audio samples are available at https://kkksuper.github.io/FleSpeech/
format Preprint
id arxiv_https___arxiv_org_abs_2501_04644
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle FleSpeech: Flexibly Controllable Speech Generation with Various Prompts
Li, Hanzhao
Li, Yuke
Wang, Xinsheng
Hu, Jingbin
Xie, Qicong
Yang, Shan
Xie, Lei
Audio and Speech Processing
Sound
Controllable speech generation methods typically rely on single or fixed prompts, hindering creativity and flexibility. These limitations make it difficult to meet specific user needs in certain scenarios, such as adjusting the style while preserving a selected speaker's timbre, or choosing a style and generating a voice that matches a character's visual appearance. To overcome these challenges, we propose \textit{FleSpeech}, a novel multi-stage speech generation framework that allows for more flexible manipulation of speech attributes by integrating various forms of control. FleSpeech employs a multimodal prompt encoder that processes and unifies different text, audio, and visual prompts into a cohesive representation. This approach enhances the adaptability of speech synthesis and supports creative and precise control over the generated speech. Additionally, we develop a data collection pipeline for multimodal datasets to facilitate further research and applications in this field. Comprehensive subjective and objective experiments demonstrate the effectiveness of FleSpeech. Audio samples are available at https://kkksuper.github.io/FleSpeech/
title FleSpeech: Flexibly Controllable Speech Generation with Various Prompts
topic Audio and Speech Processing
Sound
url https://arxiv.org/abs/2501.04644