no code implementations • 5 Sep 2023 • Yichong Leng, Zhifang Guo, Kai Shen, Xu Tan, Zeqian Ju, Yanqing Liu, Yufei Liu, Dongchao Yang, Leying Zhang, Kaitao Song, Lei He, Xiang-Yang Li, Sheng Zhao, Tao Qin, Jiang Bian
TTS approaches based on the text prompt face two main challenges: 1) the one-to-many problem, where not all details about voice variability can be described in the text prompt, and 2) the limited availability of text prompt datasets, where vendors and large cost of data labeling are required to write text prompts for speech.
no code implementations • 23 Aug 2023 • Zhifang Guo, Jianguo Mao, Rui Tao, Long Yan, Kazushige Ouchi, Hong Liu, Xiangdong Wang
To address this issue, we propose a novel model that enhances the controllability of existing pre-trained text-to-audio models by incorporating additional conditions including content (timestamp) and style (pitch contour and energy contour) as supplements to the text.
no code implementations • 22 Aug 2023 • Hualei Wang, Jianguo Mao, Zhifang Guo, Jiarui Wan, Hong Liu, Xiangdong Wang
Recently, the ability of language models (LMs) has attracted increasing attention in visual cross-modality.
no code implementations • 22 Nov 2022 • Zhifang Guo, Yichong Leng, Yihan Wu, Sheng Zhao, Xu Tan
Thus, we develop a text-to-speech (TTS) system (dubbed as PromptTTS) that takes a prompt with both style and content descriptions as input to synthesize the corresponding speech.
1 code implementation • 18 Oct 2022 • Yiming Li, Zhifang Guo, Zhirong Ye, Xiangdong Wang, Hong Liu, Yueliang Qian, Rui Tao, Long Yan, Kazushige Ouchi
For the frame-wise model, the ICT-TOSHIBA system of DCASE 2021 Task 4 is used.