1.2k citations · 7.6k across the 154 of their papers we have counts for
13 papers · 1 filter
Museformer: Transformer with Fine- and Coarse-Grained Attention for Music Generation
Botao Yu, Peiling Lu, Rui Wang +6
Symbolic music generation aims to generate music scores automatically. A recent trend is to use Transformer or its variants in music generation, which is, however, suboptimal, beca…
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…
Re-creation of Creations: A New Paradigm for Lyric-to-Melody Generation
Ang Lv, Xu Tan, Tao Qin +2
Lyric-to-melody generation is an important task in songwriting, and is also quite challenging due to its unique characteristics: the generated melodies should not only follow good…
ReLyMe: Improving Lyric-to-Melody Generation by Incorporating Lyric-Melody Relationships
Chen Zhang, Luchin Chang, Songruoyao Wu +4
Lyric-to-melody generation, which generates melody according to given lyrics, is one of the most important automatic music composition tasks. With the rapid development of deep lea…
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…
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…
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…
Cross-domain Speech Recognition with Unsupervised Character-level Distribution Matching
Wenxin Hou, Jindong Wang, Xu Tan +2
End-to-end automatic speech recognition (ASR) can achieve promising performance with large-scale training data. However, it is known that domain mismatch between training and testi…
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…
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…