4 papers
ARIMA: Reconstruction-Grounded Predictive Representation Learning for Symbolic Music
Mingyang Yao, Zhaoxiang Feng
Self-supervised learning for symbolic music has advanced largely through token-level pretraining, but such representations remain tied to tokenizer-specific sequences and often pro…
Composer Vector: Style-steering Symbolic Music Generation in a Latent Space
Xunyi Jiang, Mingyang Yao, Jingyue Huang +1
Symbolic music generation has made significant progress, yet achieving fine-grained and flexible control over composer style remains challenging. Existing training-based methods fo…
BACHI: Boundary-Aware Symbolic Chord Recognition Through Masked Iterative Decoding on Pop and Classical Music
Mingyang Yao, Ke Chen, Shlomo Dubnov +1
Automatic chord recognition (ACR) via deep learning models has gradually achieved promising recognition accuracy, yet two key challenges remain. First, prior work has primarily foc…
From Generality to Mastery: Composer-Style Symbolic Music Generation via Large-Scale Pre-training
Mingyang Yao, Ke Chen
Despite progress in controllable symbolic music generation, data scarcity remains a challenge for certain control modalities. Composer-style music generation is a prime example, as…