578 citations · 2.9k across the 69 of their papers we have counts for
7 papers · 2 filters
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…
TeleMelody: Lyric-to-Melody Generation with a Template-Based Two-Stage Method
Zeqian Ju, Peiling Lu, Xu Tan +7
Lyric-to-melody generation is an important task in automatic songwriting. Previous lyric-to-melody generation systems usually adopt end-to-end models that directly generate melodie…
DeepRapper: Neural Rap Generation with Rhyme and Rhythm Modeling
Lanqing Xue, Kaitao Song, Duocai Wu +5
Rap generation, which aims to produce lyrics and corresponding singing beats, needs to model both rhymes and rhythms. Previous works for rap generation focused on rhyming lyrics bu…
MusicBERT: Symbolic Music Understanding with Large-Scale Pre-Training
Mingliang Zeng, Xu Tan, Rui Wang +3
Symbolic music understanding, which refers to the understanding of music from the symbolic data (e.g., MIDI format, but not audio), covers many music applications such as genre cla…
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…