Efficient music identification by utilizing space-saving audio fingerprinting system

Audio fingerprints can be used to implement an efficient music identification system on a million-song library, but the system requires huge amount of memory to hold the fingerprints and indexes. Therefore, for a large-scale music library, memory imposes a restriction on the speed of music identification. In this paper, we propose an efficient music identification system which utilizes a kind of space-saving audio fingerprints. For saving space, original fingerprints are sub-sampled and only one quarter of the original data is reserved. In this way, memory requirement is much decreased and the search speed is significantly increased while the robustness and reliability are well preserved. Extensive experiments have been conducted to compare our system with a previous method, and the results show that our system requires much less memory, runs faster and achieves comparable accuracy for a large-scale database.