pyAMPACT: A Score-Audio Alignment Toolkit for Performance Data Estimation and Multi-modal Processing
December 06, 2024 ยท Declared Dead ยท ๐ arXiv.org
"No code URL or promise found in abstract"
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Authors
Johanna Devaney, Daniel McKemie, Alex Morgan
arXiv ID
2412.05436
Category
cs.SD: Sound
Cross-listed
cs.MM,
eess.AS
Citations
1
Venue
arXiv.org
Last Checked
4 months ago
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.
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