515 citations · 1.2k across the 53 of their papers we have counts for
11 papers · 1 filter
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…
SongMASS: Automatic Song Writing with Pre-training and Alignment Constraint
Zhonghao Sheng, Kaitao Song, Xu Tan +4
Automatic song writing aims to compose a song (lyric and/or melody) by machine, which is an interesting topic in both academia and industry. In automatic song writing, lyric-to-mel…
PopMAG: Pop Music Accompaniment Generation
Yi Ren, Jinzheng He, Xu Tan +3
In pop music, accompaniments are usually played by multiple instruments (tracks) such as drum, bass, string and guitar, and can make a song more expressive and contagious by arrang…
LRSpeech: Extremely Low-Resource Speech Synthesis and Recognition
Jin Xu, Xu Tan, Yi Ren +4
Speech synthesis (text to speech, TTS) and recognition (automatic speech recognition, ASR) are important speech tasks, and require a large amount of text and speech pairs for model…
FastLR: Non-Autoregressive Lipreading Model with Integrate-and-Fire
Jinglin Liu, Yi Ren, Zhou Zhao +3
Lipreading is an impressive technique and there has been a definite improvement of accuracy in recent years. However, existing methods for lipreading mainly build on autoregressive…
MultiSpeech: Multi-Speaker Text to Speech with Transformer
Mingjian Chen, Xu Tan, Yi Ren +5
Transformer-based text to speech (TTS) model (e.g., Transformer TTS~\cite{li2019neural}, FastSpeech~\cite{ren2019fastspeech}) has shown the advantages of training and inference eff…
Task-Level Curriculum Learning for Non-Autoregressive Neural Machine Translation
Jinglin Liu, Yi Ren, Xu Tan +4
Non-autoregressive translation (NAT) achieves faster inference speed but at the cost of worse accuracy compared with autoregressive translation (AT). Since AT and NAT can share mod…
DeepSinger: Singing Voice Synthesis with Data Mined From the Web
Yi Ren, Xu Tan, Tao Qin +3
In this paper, we develop DeepSinger, a multi-lingual multi-singer singing voice synthesis (SVS) system, which is built from scratch using singing training data mined from music we…
UWSpeech: Speech to Speech Translation for Unwritten Languages
Chen Zhang, Xu Tan, Yi Ren +3
Existing speech to speech translation systems heavily rely on the text of target language: they usually translate source language either to target text and then synthesize target s…
FastSpeech 2: Fast and High-Quality End-to-End Text to Speech
Yi Ren, Chenxu Hu, Xu Tan +4
Non-autoregressive text to speech (TTS) models such as FastSpeech can synthesize speech significantly faster than previous autoregressive models with comparable quality. The traini…
A Study of Non-autoregressive Model for Sequence Generation
Yi Ren, Jinglin Liu, Xu Tan +3
Non-autoregressive (NAR) models generate all the tokens of a sequence in parallel, resulting in faster generation speed compared to their autoregressive (AR) counterparts but at th…