Abstract

In radio broadcasting, the crucial task of monitoring becomes evident for protecting musical work copyrights and ensuring the fair distribution of royalties. Manual monitoring, due to its time-consuming and unreliable nature, necessitates an automated approach. The challenges in automated monitoring arise mainly from the practice of broadcast stations remastering songs before airing. These alterations introduce complexities that complicate the identification process for existing music identification techniques. This paper tackles this challenge by exploring the feasibility of employing computer vision techniques on STFT spectrograms from ongoing audio streams. The objective is to identify similar spectrogram representations by comparing them with previously registered key features extracted from STFT spectrograms generated for original song tracks. This aims to unveil the identity of content being broadcast on radio and, consequently, safeguard the rightful ownership of copyrighted songs. The proposed approach achieved an accuracy of over 97% for tempo alterations up to 20% and over 95% accuracy for pitch alterations up to 20%.