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

TL;DR

pyAMPACT is a Python toolkit that aligns symbolic and audio music data to estimate performance parameters and supports multi-modal analysis linking annotations with audio and symbolic representations.

Contribution

It introduces a versatile toolkit capable of score-informed performance data estimation and multi-modal linking between symbolic and audio music representations.

Findings

Supports various symbolic formats and outputs MEI-formatted files.

Estimates tuning, dynamics, and timbre parameters from audio.

Enables multi-modal investigations linking annotations to audio.

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.