Beat Tracking

Getting a computer music system to listen to a performance and derive the tempo and position of beats.
See also Music Understanding

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``Following an Improvisation in Real Time"
This is where I got started. Bernard Mont-Reynaud is mostly responsible for the beat-tracking work described in this paper. Our simple efforts here are based on earlier work by Bernard and by Longuet-Higgins.

Allen and Dannenberg, ``Tracking Musical Beats in Real Time,'' in 1990 International Computer Music Conference, International Computer Music Association (September 1990), pp. 140-143.

This work addressed problems that were encountered in previous work (Dannenberg and Mont-Reynaud, see above). We used a simple model that seems to underly just about every beat-tracking (and phase-locked loop) system: when a note onset is earlier than predicted, increase the tempo, and when the onset is later than expected, decrease the tempo. The two parameters are "how much to increase/decrease" and "at what deviation do you want to just ignore note onsets rather than try to adjust to match them." My system with Mont-Reynaud did not work well, but it seemed to be very sensitive to these parameters. Paul Allen and I systematically explored the parameter space and showed that, at least for our test set, no parameter combination would work well.

We then set out to do better by using beam search to track multiple hypotheses about the tempo and phase. This approach has been very influential, especially in David Rosenthal's work. There is a longer, unpublished version of this paper (see below).

[Adobe Acrobat (PDF) Version.] [Postscript Version.]


Allen and Dannenberg, ``Tracking Musical Beats in Real Time," unpublished manuscript, 1990.
This is the full version of this paper. A shorter version was published in the 1990 ICMC (see above). I am not quite sure of the sequence, but I believe that this version came first, and then we cut it down to meet the page restrictions of the conference proceedings.

[Adobe Acrobat (PDF) Version.] [Postscript Version.]


Dannenberg, ``Toward Automated Holistic Beat Tracking, Music Analysis, and Understanding,'' in ISMIR 2005 6th International Conference on Music Information Retrieval Proceedings, London: Queen Mary, University of London, (2005), pp. 366-373.
ABSTRACT:Most music processing attempts to focus on one particular feature or structural element such as pitch, beat location, tempo, or genre. This hierarchical approach, in which music is separated into elements that are analyzed independently, is convenient for the scientific researcher, but is at odds with intuition about music perception. Music is interconnected at many levels, and the interplay of melody, harmony, and rhythm are important in perception. As a first step toward more holistic music analysis, music structure is used to constrain a beat tracking program. With structural information, the simple beat tracker, working with audio input, shows a large improvement. The implications of this work for other music analysis problems are discussed.

[Adobe Acrobat (PDF) Version.]


Dannenberg and Hu, ``Bootstrap Learning for Accurate Onset Detection," Machine Learning 65(2-3) (December 2006), pp. 457-471.

Hu and Dannenberg, ``A Bootstrap Method for Training an Accurate Audio Segmenter,'' in Proceedings of the Sixth International Conference on Music Information Retrieval, London England: Queen Mary, University of London & Goldsmiths College, University of London, (2005), pp. 223-229.

Computer alignment is used to get an initial estimate for the locations of onsets (you must have a MIDI or symbolic score of the audio). Using these locations as training data, machine learning is used to build an onset detector. The onset detector can then be used to create its own training data, thus "pulling itself up by its own bootstraps," resulting in further improvements.

These two papers are similar, but the Journal version has more detail and also reports on some experiments with polyphonic onset detection.