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Creators/Authors contains: "McKemie, Daniel"

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  1. ; ; (, 2025 International Computer Music Conference)
    pyAMPACT (Python-based Automatic Music Performance Analysis and Comparison Toolkit) links symbolic and audio music representations to facilitate score-informed estimation of performance data from audio. It can read a range of symbolic formats and can output note-linked audio descriptors/performance data into MEI-formatted files. pyAMPACT uses score alignment to calculate time-frequency regions of importance for each note in the symbolic representation from which it estimates a range of parameters from the corresponding audio. These include frame-wise and note-level 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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    Free, publicly-accessible full text available June 11, 2026