20 citations · 122 across the 18 of their papers we have counts for
14 papers · 1 filter
SnakeGAN: A Universal Vocoder Leveraging DDSP Prior Knowledge and Periodic Inductive Bias
Sipan Li, Songxiang Liu, Luwen Zhang +5
Generative adversarial network (GAN)-based neural vocoders have been widely used in audio synthesis tasks due to their high generation quality, efficient inference, and small compu…
Speaker Identity Preservation in Dysarthric Speech Reconstruction by Adversarial Speaker Adaptation
Disong Wang, Songxiang Liu, Xixin Wu +4
Dysarthric speech reconstruction (DSR), which aims to improve the quality of dysarthric speech, remains a challenge, not only because we need to restore the speech to be normal, bu…
DiffGAN-TTS: High-Fidelity and Efficient Text-to-Speech with Denoising Diffusion GANs
Songxiang Liu, Dan Su, Dong Yu
Denoising diffusion probabilistic models (DDPMs) are expressive generative models that have been used to solve a variety of speech synthesis problems. However, because of their hig…
Meta-Voice: Fast few-shot style transfer for expressive voice cloning using meta learning
Songxiang Liu, Dan Su, Dong Yu
The task of few-shot style transfer for voice cloning in text-to-speech (TTS) synthesis aims at transferring speaking styles of an arbitrary source speaker to a target speaker's vo…
Referee: Towards reference-free cross-speaker style transfer with low-quality data for expressive speech synthesis
Songxiang Liu, Shan Yang, Dan Su +1
Cross-speaker style transfer (CSST) in text-to-speech (TTS) synthesis aims at transferring a speaking style to the synthesised speech in a target speaker's voice. Most previous CSS…
DiffSVC: A Diffusion Probabilistic Model for Singing Voice Conversion
Songxiang Liu, Yuewen Cao, Dan Su +1
Singing voice conversion (SVC) is one promising technique which can enrich the way of human-computer interaction by endowing a computer the ability to produce high-fidelity and exp…