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

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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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