515 citations · 1.2k across the 46 of their papers we have counts for
10 papers · 1 filter
An End-to-End Multi-Module Audio Deepfake Generation System for ADD Challenge 2023
Sheng Zhao, Qilong Yuan, Yibo Duan +1
The task of synthetic speech generation is to generate language content from a given text, then simulating fake human voice.The key factors that determine the effect of synthetic s…
AUDIT: Audio Editing by Following Instructions with Latent Diffusion Models
Yuancheng Wang, Zeqian Ju, Xu Tan +4
Audio editing is applicable for various purposes, such as adding background sound effects, replacing a musical instrument, and repairing damaged audio. Recently, some diffusion-bas…
Improving Contextual Spelling Correction by External Acoustics Attention and Semantic Aware Data Augmentation
Xiaoqiang Wang, Yanqing Liu, Jinyu Li +1
We previously proposed contextual spelling correction (CSC) to correct the output of end-to-end (E2E) automatic speech recognition (ASR) models with contextual information such as…
MeloForm: Generating Melody with Musical Form based on Expert Systems and Neural Networks
Peiling Lu, Xu Tan, Botao Yu +3
Human usually composes music by organizing elements according to the musical form to express music ideas. However, for neural network-based music generation, it is difficult to do…
DelightfulTTS 2: End-to-End Speech Synthesis with Adversarial Vector-Quantized Auto-Encoders
Yanqing Liu, Ruiqing Xue, Lei He +2
Current text to speech (TTS) systems usually leverage a cascaded acoustic model and vocoder pipeline with mel-spectrograms as the intermediate representations, which suffer from tw…
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…
MBNet: MOS Prediction for Synthesized Speech with Mean-Bias Network
Yichong Leng, Xu Tan, Sheng Zhao +3
Mean opinion score (MOS) is a popular subjective metric to assess the quality of synthesized speech, and usually involves multiple human judges to evaluate each speech utterance. T…
LightSpeech: Lightweight and Fast Text to Speech with Neural Architecture Search
Renqian Luo, Xu Tan, Rui Wang +5
Text to speech (TTS) has been broadly used to synthesize natural and intelligible speech in different scenarios. Deploying TTS in various end devices such as mobile phones or embed…