16 citations · 85 across the 17 of their papers we have counts for
17 papers
C2G2: Controllable Co-speech Gesture Generation with Latent Diffusion Model
Longbin Ji, Pengfei Wei, Yi Ren +3
Co-speech gesture generation is crucial for automatic digital avatar animation. However, existing methods suffer from issues such as unstable training and temporal inconsistency, p…
Ada-TTA: Towards Adaptive High-Quality Text-to-Talking Avatar Synthesis
Zhenhui Ye, Ziyue Jiang, Yi Ren +5
We are interested in a novel task, namely low-resource text-to-talking avatar. Given only a few-minute-long talking person video with the audio track as the training data and arbit…
Mega-TTS 2: Boosting Prompting Mechanisms for Zero-Shot Speech Synthesis
Ziyue Jiang, Jinglin Liu, Yi Ren +10
Zero-shot text-to-speech (TTS) aims to synthesize voices with unseen speech prompts, which significantly reduces the data and computation requirements for voice cloning by skipping…
Mega-TTS: Zero-Shot Text-to-Speech at Scale with Intrinsic Inductive Bias
Ziyue Jiang, Yi Ren, Zhenhui Ye +9
Scaling text-to-speech to a large and wild dataset has been proven to be highly effective in achieving timbre and speech style generalization, particularly in zero-shot TTS. Howeve…
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…
EE-TTS: Emphatic Expressive TTS with Linguistic Information
Yi Zhong, Chen Zhang, Xule Liu +4
While Current TTS systems perform well in synthesizing high-quality speech, producing highly expressive speech remains a challenge. Emphasis, as a critical factor in determining th…