Matchmaker: A Python library for Real-time Music Alignment
Jiyun Park (KAIST)*, Carlos Eduardo Cancino-Chacón (Johannes Kepler University Linz), Taegyun Kwon (KAIST), Juhan Nam (KAIST)
This paper will be presented in person
Music alignment is a fundamental MIR task, and real-time music alignment is a necessary component of many interactive applications (e.g., automatic accompaniment systems, automatic page turning). This paper introduces Matchmaker, an open source Python library for real-time music alignment. Unlike offline alignment methods, for which state-of-the-art implementations are publicly available, real-time (online) methods have no standard implementation, forcing researchers and developers to build them from scratch for their projects. We aim to provide efficient reference implementations of score followers for use in real-time applications which can be easily integrated into existing projects. We also aim to provide guidelines to help researchers and developers select an appropriate configuration for their applications.