Beat Tracking with a Two State Model

In this paper we apply a two state switching model to the problem of audio based beat tracking. Our analysis is based around the generation and application of adaptively weighted comb filterbank structures to extract beat timing information from the midlevel representation of an input audio signal known as the onset detection function [1]. We evaluate our system using a previously published dataset [2] and in performing a direct comparison with the current state of the art, present comparable results.