Music identification is an effective tool that enables multimedia players to extract a distinct statistical digest of the played content, look up into a music database using the extracted unique identifier, and then take advantage of the services available for that particular content. In this paper, we introduce Beat-IDs, the first music identification system that creates the digest of the music clip by understanding the basic structure of every musical piece: its beat. A Beat-ID is created in two steps: first, the system detects the average beat period of a given music clip using a mod-ified EM algorithm and then, it analyzes the statistical properties of the clip with respect to the detected beats. The extracted 32-byte Beat-ID contains two components: the length of the average beat period and a compressed statistical digest of signal's energy distribution in an average beat period. Finally, we introduce an algorithm for matching Beat-IDs that quantifies the matching accuracy between two music identifiers using an error analysis. In this paper, the properties of Beat-IDs are demonstrated using a relatively small database of audio clips.
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