21 citations · 53 across the 16 of their papers we have counts for
6 papers · 1 filter
T2A-Feedback: Improving Basic Capabilities of Text-to-Audio Generation via Fine-grained AI Feedback
Zehan Wang, Ke Lei, Chen Zhu +8
Text-to-audio (T2A) generation has achieved remarkable progress in generating a variety of audio outputs from language prompts. However, current state-of-the-art T2A models still s…
MulliVC: Multi-lingual Voice Conversion With Cycle Consistency
Jiawei Huang, Chen Zhang, Yi Ren +6
Voice conversion aims to modify the source speaker's voice to resemble the target speaker while preserving the original speech content. Despite notable advancements in voice conver…
Make-An-Audio 2: Temporal-Enhanced Text-to-Audio Generation
Jiawei Huang, Yi Ren, Rongjie Huang +7
Large diffusion models have been successful in text-to-audio (T2A) synthesis tasks, but they often suffer from common issues such as semantic misalignment and poor temporal consist…
RMSSinger: Realistic-Music-Score based Singing Voice Synthesis
Jinzheng He, Jinglin Liu, Zhenhui Ye +4
We are interested in a challenging task, Realistic-Music-Score based Singing Voice Synthesis (RMS-SVS). RMS-SVS aims to generate high-quality singing voices given realistic music s…
Make-An-Audio: Text-To-Audio Generation with Prompt-Enhanced Diffusion Models
Rongjie Huang, Jiawei Huang, Dongchao Yang +7
Large-scale multimodal generative modeling has created milestones in text-to-image and text-to-video generation. Its application to audio still lags behind for two main reasons: th…
SyntaSpeech: Syntax-Aware Generative Adversarial Text-to-Speech
Zhenhui Ye, Zhou Zhao, Yi Ren +1
The recent progress in non-autoregressive text-to-speech (NAR-TTS) has made fast and high-quality speech synthesis possible. However, current NAR-TTS models usually use phoneme seq…