Enhancement of Beat Tracking in String Quartet Music Analysis Based on the Teager-Kaiser Energy Operator

Beat detection systems are widely used in music information retrieval (MIR) research field for the computation of tempo and beat positions in audio signals. One of the most important parts of these systems is the onset detection function. The aim of this study is to introduce an enhancement of a conventional onset detector and employ it in a beat tracking system that could be utilized for an analysis of interpretation and performance changes in string quartets. The enhancement is based on the Teager-Kaiser energy operator (TKEO), which pre-processes input audio signal before spectral flux calculation. The proposed approach is firstly evaluated in terms of ability to estimate global tempo (GT) of a given audio track. Next, the accuracy of the GT estimation is compared with a manually-labelled reference dataset. Then, this system was tested on the first motif of the string quartet database. Results suggest that the TKEO could improve accuracy of the GT estimation. Average deviation from the reference tempo in the string quartet is 8.29%, which slightly improves the conventional methodology, where the deviance is 8.96%. This study has a pilot character and provides some suggestions of the beat tracking system enhancement.