2 citations · 2 across the 9 of their papers we have counts for
5 papers · 1 filter
MAJEPPA: Morphing and Assessing in a Unified Piano Performance Space
Jinwen Zhou, Huan Zhang, Weixi Zhai +3
We present MAJEPPA, a self-supervised framework to learn piano performance representations that span the full skill spectrum, from beginner practice sessions to virtuoso concert re…
From Aesthetics to Human Preferences: Comparative Perspectives of Evaluating Text-to-Music Systems
Huan Zhang, Jinhua Liang, Huy Phan +2
Evaluating generative models remains a fundamental challenge, particularly when the goal is to reflect human preferences. In this paper, we use music generation as a case study to…
Hierarchical Symbolic Pop Music Generation with Graph Neural Networks
Wen Qing Lim, Jinhua Liang, Huan Zhang
Music is inherently made up of complex structures, and representing them as graphs helps to capture multiple levels of relationships. While music generation has been explored using…
From Audio Encoders to Piano Judges: Benchmarking Performance Understanding for Solo Piano
Huan Zhang, Jinhua Liang, Simon Dixon
Our study investigates an approach for understanding musical performances through the lens of audio encoding models, focusing on the domain of solo Western classical piano music. C…
DExter: Learning and Controlling Performance Expression with Diffusion Models
Huan Zhang, Shreyan Chowdhury, Carlos Eduardo Cancino-Chacón +3
In the pursuit of developing expressive music performance models using artificial intelligence, this paper introduces DExter, a new approach leveraging diffusion probabilistic mode…