Beat Tracking System Based On A Neural Network

Abstract

This thesis deals with systems for tempo and beat detection in music recordings, whosefunctionality is based on neural networks. The basic structure of such systems is briefly described andthe emphasis is then placed on a comparison of recurrent and temporal convolutional networks, whichhave proven to be the most suitable for this task. The main outcome of this work is then proposaland comparison of modified temporal convolutional network with other state-of-the-art networks ina beat tracking system. The results suggest that simplification in existing architectures could benefitfrom faster training times, while it maintains or slightly improves the accuracy of a detection system.