This paper proposes a Gaussian mixture model (GMM)-based music discrimination system for mobile broadcasting receivers. The objective of the system is automatically archiving music signals from audio broadcasting programs that are normally mixed with human voices, acoustic noises, commercial advertisements, and so on. To enhance the robustness of the system performance and to sharply cut the starting/ending-point of the recording, we also introduce a post-processing module whose features consist of signal duration, energy dynamics, and local variation of feature statistics. Experimental results to various input signals verify the superiority of the proposed system.
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