7 citations · 17 across the 7 of their papers we have counts for
8 papers
VarietySound: Timbre-Controllable Video to Sound Generation via Unsupervised Information Disentanglement
Chenye Cui, Yi Ren, Jinglin Liu +2
Video to sound generation aims to generate realistic and natural sound given a video input. However, previous video-to-sound generation methods can only generate a random or averag…
Learning the Beauty in Songs: Neural Singing Voice Beautifier
Jinglin Liu, Chengxi Li, Yi Ren +2
We are interested in a novel task, singing voice beautifying (SVB). Given the singing voice of an amateur singer, SVB aims to improve the intonation and vocal tone of the voice, wh…
MR-SVS: Singing Voice Synthesis with Multi-Reference Encoder
Shoutong Wang, Jinglin Liu, Yi Ren +3
Multi-speaker singing voice synthesis is to generate the singing voice sung by different speakers. To generalize to new speakers, previous zero-shot singing adaptation methods obta…
SimulLR: Simultaneous Lip Reading Transducer with Attention-Guided Adaptive Memory
Zhijie Lin, Zhou Zhao, Haoyuan Li +4
Lip reading, aiming to recognize spoken sentences according to the given video of lip movements without relying on the audio stream, has attracted great interest due to its applica…
EMOVIE: A Mandarin Emotion Speech Dataset with a Simple Emotional Text-to-Speech Model
Chenye Cui, Yi Ren, Jinglin Liu +4
Recently, there has been an increasing interest in neural speech synthesis. While the deep neural network achieves the state-of-the-art result in text-to-speech (TTS) tasks, how to…
DenoiSpeech: Denoising Text to Speech with Frame-Level Noise Modeling
Chen Zhang, Yi Ren, Xu Tan +5
While neural-based text to speech (TTS) models can synthesize natural and intelligible voice, they usually require high-quality speech data, which is costly to collect. In many sce…