Automated Real-Time Beat Tracking: Response Time and Confidence Analysis
This is the accompanying website for the Bachelor Thesis [1].
Rico Rosenbusch Automated Real-Time Beat Tracking: Response Time and Confidence Analysis Bachelor Thesis, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), 2024.
Demo
@misc{Rosenbusch24_ARTBeaT_Bachelor_Thesis,
title = {Automated Real-Time Beat Tracking: Response Time and Confidence Analysis},
author = {Rico Rosenbusch},
year = {2024},
note = {Bachelor Thesis, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU)},
url-demo = {https://audiolabs-erlangen.de/resources/MIR/2024-ARTBeaT}
}
Abstract
Real-time beat tracking remains a challenging task for music information retrieval. This thesis presents
a comparative analysis of human and machine real-time beat tracking performance. The algorithm used is
based on the predominant local pulse (PLP) procedure. For comparing the results of the algorithm and
humans with each other, their performances are evaluated on a dataset of 25 short unfamiliar pieces of
music, containing rhythmic challenges such as tempo changes, metric ambiguity, or syncopated rhythms.
A web-based listening test was conducted to collect real-time annotations from participants tapping
along to each example. The metrics used to evaluate the examples annotated by the algorithm and users
include F-measure, response time, and confidence measurements. Note that the algorithm is not compared
to individuals but to the average performance of all users, obtained by using a kernel density
estimation (KDE) technique.
Parameter tuning is also explored, showing the effect of kernel size on the algorithm's stability and
responsiveness. Differences in methodology, strengths, and limitations are identified between human and
machine rhythmic cognition.
The analysis provides new insights into more natural modeling of human timing perception. Humans show
faster adaptation after tempo changes but are also briefly confused by deceptive rhythms. With a
well-tuned set of parameters, the algorithm can match or exceed human consistency on some rhythms.
Overall, this work advances understanding of real-time beat tracking through direct comparison with
human annotation data. The findings have implications for improving computational rhythmic analysis and
further outlining similarities and divergences between human and machine rhythmic cognition.
Analysis Example
The figure presents the analysis of a single audio example from the dataset, highlighting both the algorithm's beat tracking output and the human user annotations collected through a listening test.
Figure 4.21: Visualization of important audio, online PLP and user annotation data of audio example 13_ARTBeaT_TempoA_180to120.wav. (a) Waveform. (b) Spectrogram. (c) Novelty function. (d) Peaks detected by online PLP algorithm. (e) β-confidence. (f) Histogram of user annotations, with a Gaussian KDE and its peaks plotted over it. (g) user confidence. (h) user recall ratio (URR).
Dataset
We present the dataset "ARTBeaT," an acronym for the title of this bachelor thesis, "Automated
Real-Time Beat Tracking."
Download:
ARTBeaT
Dataset by Rico Rosenbusch is licensed under CC BY 4.0
Files
The files are named using the following pattern:
{ID}_ARTBeaT_{Category}_{Name}.wav, as shown in the table below.
Beat played by electronic instruments starting out in 4/4 at 85 BPM, changing to 6/4 in 127.5, with the bass
and kick pattern staying the same, while the hihat and snare pattern change, enforcing the 6/4 feel.
Normal drumbeat in 4/4 for the first half, in the second half the ride cymbal is added playing on the second
16th note of every beat, shifting the rhythmic perception.
Online PLP annotation with parameters resulting in best F-measure
To listen to the sonified data, press the yellow power button in the middle of the respective trackswitcher and then
press the play button or spacebar.
Select the annotations you want to listen to from the tracklist below the image.
Audio 02
Starts with an arpeggio played on a synthesizer, continues in same tempo and measure with added instruments.
Beat played by electronic instruments starting out in 4/4 at 85 BPM, changing to 6/4 in 127.5, with the bass and kick
pattern staying the same, while the hihat and snare pattern change, enforcing the 6/4 feel.
Normal drumbeat in 4/4 for the first half, in the second half the ride cymbal is added playing on the second 16th
note of every beat, shifting the rhythmic perception.
Rico Rosenbusch Automated Real-Time Beat Tracking: Response Time and Confidence Analysis Bachelor Thesis, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), 2024.
Demo
@misc{Rosenbusch24_ARTBeaT_Bachelor_Thesis,
title = {Automated Real-Time Beat Tracking: Response Time and Confidence Analysis},
author = {Rico Rosenbusch},
year = {2024},
note = {Bachelor Thesis, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU)},
url-demo = {https://audiolabs-erlangen.de/resources/MIR/2024-ARTBeaT}
}
Peter Meier, Ching-Yu Chiu, and Meinard Müller A Real-Time Beat Tracking System with Zero Latency and Enhanced Controllability Transactions of the International Society for Music Information Retrieval (TISMIR), 7(1): 213–227, 2024.
Demo
DOI
@article{MeierCM24_RealTimePLP_TISMIR,
author = {Peter Meier and Ching-Yu Chiu and Meinard M{\"u}ller},
title = {{A} Real-Time Beat Tracking System with Zero Latency and Enhanced Controllability},
journal = {Transactions of the International Society for Music Information Retrieval ({TISMIR})},
year = {2024},
volume = {7},
number = {1},
pages = {213--227},
doi = {10.5334/tismir.189},
url-demo = {https://audiolabs-erlangen.de/resources/MIR/2024-TISMIR-RealTimePLP}
}
Peter Meier, Simon Schwär, and Meinard Müller A Real-Time Approach for Estimating Pulse Tracking Parameters for Beat-Synchronous Audio Effects In Proceedings of the International Conference on Digital Audio Effects (DAFx): 314–321, 2024.
Demo
@inproceedings{MeierSM24_RealTimePulseParameters_DAFX,
author = {Peter Meier and Simon Schw{\"a}r and Meinard M{\"u}ller},
title = {{A} Real-Time Approach for Estimating Pulse Tracking Parameters for Beat-Synchronous Audio Effects},
booktitle = {Proceedings of the International Conference on Digital Audio Effects ({DAFx})},
address = {Guildford, Surrey, {UK}},
year = {2024},
pages = {314--321},
url-demo = {https://audiolabs-erlangen.de/resources/MIR/2024-DAFx-RealTimePLP}
}