Tutorial scope and prerequisites¶
The scope of the material presented in the tutorial can be addressed in two ways: technical and musical.
From the technical perspective our primary focus is in providing hands-on experience of current state of the art deep learning approaches. To this end, we depart from historical signal processing approaches and move quickly from these into deep learning based approaches. In this way, we only touch upon the broader, multi-disciplinary context of the phenonema of the rhythmic and metrical structure of music and limit insights in relation to music cognition, computational neuroscience, and music theory. In sum, this tutorial can be primarily understood as a data-driven approach to the estimation of tempo, beat, and downbeats from musical audio signals.
It is important to note that this tutorial is not intended to be exhaustive in its coverage of all existing approaches, and furthermore places greater emphasis on more recent research covering the last 5 - 10 years.
Tip
For anyone wanting a more detailed look at earlier approaches we highly recommend the ISMIR 2006 tutorial on Computational Rhythm Description conducted by not one but two former ISMIR Presidents: Fabien Gouyon and Simon Dixon.
From the musical perspective we also restrict ourselves largely to musical content from a Western perspective. This is in no way an attempt to diminish or downplay the importance of non-Western musical traditions, but rather it is a reflection of the knowledge-base and backgrounds of the presenters.
Concerning prerequisites for this tutorial, some technical expertise in the execution of python notebooks would be beneficial, although it should be possible just to click through all of the examples without that. In addition, we rely on some basic informal understanding of metrical structure in music. In structuring the content of the tutorial, we have strived for a fairly light-weight and non-technical introductory part, followed by some important theoretical constructs concerning deep learning approaches to rhythm analysis, prior to the main “hands-on” component.