An Empirical Comparison of Tempo Trackers

One of the difficulties with assessing tempo or beat tracking systems is that there is no standard corpus of data on which they can be tested. This situation is partly because the choice of data set often depends on the goals of the system, which might be, for example, automatic transcription, computer accompaniment of a human performer, or the analysis of expressive timing in musical performance. Without standard test data, there is the risk of overfitting a system to the data on which it is tested, and developing a system which is not suitable for use outside a very limited musical domain. In this paper, we use a large, publicly available set of performances of two Beatles songs recorded on a Yamaha Disklavier in order to compare two models of tempo tracking: a probabilistic model which uses a Kalman filter to estimate tempo and beat times, and a tempo tracker based on a multiagent search strategy. Both models perform extremely well on the test data, with the multiagent search achieving marginally better results. We propose two simple measures of tempo tracking difficulty, and argue that a broader set of test data is required for comprehensive testing of tempo tracking systems.