14 citations · 20 across the 14 of their papers we have counts for
4 papers · 2 filters
StyleSpeech: Self-supervised Style Enhancing with VQ-VAE-based Pre-training for Expressive Audiobook Speech Synthesis
Xueyuan Chen, Xi Wang, Shaofei Zhang +4
The expressive quality of synthesized speech for audiobooks is limited by generalized model architecture and unbalanced style distribution in the training data. To address these is…
UniAudio: An Audio Foundation Model Toward Universal Audio Generation
Dongchao Yang, Jinchuan Tian, Xu Tan +9
Large Language models (LLM) have demonstrated the capability to handle a variety of generative tasks. This paper presents the UniAudio system, which, unlike prior task-specific app…
Improving Language Model-Based Zero-Shot Text-to-Speech Synthesis with Multi-Scale Acoustic Prompts
Shun Lei, Yixuan Zhou, Liyang Chen +8
Zero-shot text-to-speech (TTS) synthesis aims to clone any unseen speaker's voice without adaptation parameters. By quantizing speech waveform into discrete acoustic tokens and mod…
QS-TTS: Towards Semi-Supervised Text-to-Speech Synthesis via Vector-Quantized Self-Supervised Speech Representation Learning
Haohan Guo, Fenglong Xie, Jiawen Kang +3
This paper proposes a novel semi-supervised TTS framework, QS-TTS, to improve TTS quality with lower supervised data requirements via Vector-Quantized Self-Supervised Speech Repres…