2021-11-11
Beat tracking is a central topic within the MIR community and an active area of research. The scientific progress in this area is mainly thanks to recent machine learning techniques. However, some machine learning approaches are black boxes, hard to understand, and often without direct control over the parameters to adjust the beat tracker. For this demo, we choose a model-based approach that is easy to understand, good for interactions, and well suited for educational purposes. In particular, we present a system for real-time interactive beat tracking based on predominant local pulse (PLP) information, as first described in Grosche et al. In the first section, we show how the PLP-based algorithm can be transformed from an offline procedure to a real-time procedure. In the second section, we present the implementation of a system that uses this real-time procedure as the centerpiece of an interactive beat tracking application.
@inproceedings{MeierKM21_RealTimeBeatTrackingSystem_ISMIR-LBD,
author = {Peter Meier and Gerhard Krump and Meinard M{\"u}ller},
title = {A Real-Time Beat Tracking System Based on Predominant Local Pulse Information},
booktitle = {Demos and Late Breaking News of the International Society for Music Information Retrieval Conference ({ISMIR})},
address = {Online},
year = {2021},
url-pdf = {https://archives.ismir.net/ismir2021/latebreaking/000021.pdf}
}