6 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…
RenderBox: Expressive Performance Rendering with Text Control
Huan Zhang, Akira Maezawa, Simon Dixon
Expressive music performance rendering involves interpreting symbolic scores with variations in timing, dynamics, articulation, and instrument-specific techniques, resulting in per…
How does the teacher rate? Observations from the NeuroPiano dataset
Huan Zhang, Vincent Cheung, Hayato Nishioka +2
This paper provides a detailed analysis of the NeuroPiano dataset, which comprise 104 audio recordings of student piano performances accompanied with 2255 textual feedback and rati…
LLaQo: Towards a Query-Based Coach in Expressive Music Performance Assessment
Huan Zhang, Vincent Cheung, Hayato Nishioka +2
Research in music understanding has extensively explored composition-level attributes such as key, genre, and instrumentation through advanced representations, leading to cross-mod…
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…