Search Results for author: Yuewen Cao

Found 4 papers, 2 papers with code

DiffSVC: A Diffusion Probabilistic Model for Singing Voice Conversion

no code implementations28 May 2021 Songxiang Liu, Yuewen Cao, Dan Su, Helen Meng

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 expressive singing voice.

Denoising Voice Conversion +1

VARA-TTS: Non-Autoregressive Text-to-Speech Synthesis based on Very Deep VAE with Residual Attention

no code implementations12 Feb 2021 Peng Liu, Yuewen Cao, Songxiang Liu, Na Hu, Guangzhi Li, Chao Weng, Dan Su

This paper proposes VARA-TTS, a non-autoregressive (non-AR) text-to-speech (TTS) model using a very deep Variational Autoencoder (VDVAE) with Residual Attention mechanism, which refines the textual-to-acoustic alignment layer-wisely.

Speech Synthesis Text-To-Speech Synthesis

FastSVC: Fast Cross-Domain Singing Voice Conversion with Feature-wise Linear Modulation

2 code implementations11 Nov 2020 Songxiang Liu, Yuewen Cao, Na Hu, Dan Su, Helen Meng

This paper presents FastSVC, a light-weight cross-domain singing voice conversion (SVC) system, which can achieve high conversion performance, with inference speed 4x faster than real-time on CPUs.

Voice Conversion

Any-to-Many Voice Conversion with Location-Relative Sequence-to-Sequence Modeling

1 code implementation6 Sep 2020 Songxiang Liu, Yuewen Cao, Disong Wang, Xixin Wu, Xunying Liu, Helen Meng

During the training stage, an encoder-decoder-based hybrid connectionist-temporal-classification-attention (CTC-attention) phoneme recognizer is trained, whose encoder has a bottle-neck layer.

feature selection speech-recognition +2

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