Advertisement detection in commercial radio channels

In this paper, real time identification of advertisement segments in a radio broadcast is performed. There are certain distinctive characteristics of advertisements that distinguish from the rest of the broadcasting information, Speech technology related to recognition of specific patterns in speech signal can characterize this distinction. Machine learning tools such as Hidden Markov Models, Artificial Neural Networks and Ensemble Method are used to classify advertisement and non-advertisement patterns. An ensemble classification technique gave a better classification performance. The system was created using blind audio segmentation for optimization of real time analysis. This work is done mainly using audio characteristics and can be extended to visual data.