10 citations · 21 across the 10 of their papers we have counts for
8 papers · 1 filter
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…
Shao: Scaling Acoustic Token Language Models Toward High-Fidelity Music Generation
Jiafeng Liu, Yuanliang Dong, Hongjia Liu +8
A common design pattern in high-quality music generation is to handle structure and fidelity in different representation spaces: a generator first models high-level structure, foll…
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…
CLaMP 3: Universal Music Information Retrieval Across Unaligned Modalities and Unseen Languages
Shangda Wu, Zhancheng Guo, Ruibin Yuan +7
CLaMP 3 is a unified framework developed to address challenges of cross-modal and cross-lingual generalization in music information retrieval. Using contrastive learning, it aligns…
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…
TunesFormer: Forming Irish Tunes with Control Codes by Bar Patching
Shangda Wu, Xiaobing Li, Feng Yu +1
This paper introduces TunesFormer, an efficient Transformer-based dual-decoder model specifically designed for the generation of melodies that adhere to user-defined musical forms.…
Symphony Generation with Permutation Invariant Language Model
Jiafeng Liu, Yuanliang Dong, Zehua Cheng +4
In this work, we propose a permutation invariant language model, SymphonyNet, as a solution for symbolic symphony music generation. We propose a novel Multi-track Multi-instrument…