2 citations · 4 across the 5 of their papers we have counts for
5 papers
TUTTI: Toward generalizable audio-to-score transcription via fully synthesized data
Jianhuai Hu, Yashan Wang, Shangda Wu +7
Generalizable Audio-to-Score (A2S) transcription is fundamentally constrained by the severe scarcity of high-quality, real-world paired data. Relying solely on existing human-annot…
NotaGen: Advancing Musicality in Symbolic Music Generation with Large Language Model Training Paradigms
Yashan Wang, Shangda Wu, Jianhuai Hu +7
We introduce NotaGen, a symbolic music generation model aiming to explore the potential of producing high-quality classical sheet music. Inspired by the success of Large Language M…
Exploring Tokenization Methods for Multitrack Sheet Music Generation
Yashan Wang, Shangda Wu, Xingjian Du +1
This study explores the tokenization of multitrack sheet music in ABC notation, introducing two methods--bar-stream and line-stream patching. We compare these methods against exist…
CLaMP 2: Multimodal Music Information Retrieval Across 101 Languages Using Large Language Models
Shangda Wu, Yashan Wang, Ruibin Yuan +12
Challenges in managing linguistic diversity and integrating various musical modalities are faced by current music information retrieval systems. These limitations reduce their effe…
MelodyT5: A Unified Score-to-Score Transformer for Symbolic Music Processing
Shangda Wu, Yashan Wang, Xiaobing Li +2
In the domain of symbolic music research, the progress of developing scalable systems has been notably hindered by the scarcity of available training data and the demand for models…