9 citations · 11 across the 6 of their papers we have counts for
6 papers
Next Tokens Denoising for Speech Synthesis
Yanqing Liu, Ruiqing Xue, Chong Zhang +7
While diffusion and autoregressive (AR) models have significantly advanced generative modeling, they each present distinct limitations. AR models, which rely on causal attention, c…
VideoDubber: Machine Translation with Speech-Aware Length Control for Video Dubbing
Yihan Wu, Junliang Guo, Xu Tan +7
Video dubbing aims to translate the original speech in a film or television program into the speech in a target language, which can be achieved with a cascaded system consisting of…
AdaSpeech 4: Adaptive Text to Speech in Zero-Shot Scenarios
Yihan Wu, Xu Tan, Bohan Li +5
Adaptive text to speech (TTS) can synthesize new voices in zero-shot scenarios efficiently, by using a well-trained source TTS model without adapting it on the speech data of new s…
DelightfulTTS: The Microsoft Speech Synthesis System for Blizzard Challenge 2021
Yanqing Liu, Zhihang Xu, Gang Wang +6
This paper describes the Microsoft end-to-end neural text to speech (TTS) system: DelightfulTTS for Blizzard Challenge 2021. The goal of this challenge is to synthesize natural and…
AdaSpeech 3: Adaptive Text to Speech for Spontaneous Style
Yuzi Yan, Xu Tan, Bohan Li +6
While recent text to speech (TTS) models perform very well in synthesizing reading-style (e.g., audiobook) speech, it is still challenging to synthesize spontaneous-style speech (e…
AdaSpeech 2: Adaptive Text to Speech with Untranscribed Data
Yuzi Yan, Xu Tan, Bohan Li +4
Text to speech (TTS) is widely used to synthesize personal voice for a target speaker, where a well-trained source TTS model is fine-tuned with few paired adaptation data (speech a…