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pyAMPACT: A Score-Audio Alignment Toolkit for Performance Data Estimation and Multi-modal Processing

Sound 2026-01-06 v2 Multimedia Audio and Speech Processing

Abstract

pyAMPACT (Python-based Automatic Music Performance Analysis and Comparison Toolkit) links symbolic and audio music representations to facilitate score-informed estimation of performance data in audio as well as general linking of symbolic and audio music representations with a variety of annotations. pyAMPACT can read a range of symbolic formats and can output note-linked audio descriptors/performance data into MEI-formatted files. The audio analysis uses score alignment to calculate time-frequency regions of importance for each note in the symbolic representation from which to estimate a range of parameters. These include tuning-, dynamics-, and timbre-related performance descriptors, with timing-related information available from the score alignment. Beyond performance data estimation, pyAMPACT also facilitates multi-modal investigations through its infrastructure for linking symbolic representations and annotations to audio.

Keywords

Cite

@article{arxiv.2412.05436,
  title  = {pyAMPACT: A Score-Audio Alignment Toolkit for Performance Data Estimation and Multi-modal Processing},
  author = {Johanna Devaney and Daniel McKemie and Alex Morgan},
  journal= {arXiv preprint arXiv:2412.05436},
  year   = {2026}
}

Comments

Proceedings of the 2025 International Computer Music Conference

R2 v1 2026-06-28T20:26:15.292Z