Project Abstract:

Music information retrieval is becoming very important with the ever-increasing growth of music content in digital libraries, peer-to-peer systems and the internet. While it is easy to quantize music into a discrete string representation, retrieval by content requires (approximate) sub-string matching, which is hard.

We propose a novel system, called MUSIG, that uses compact MUsic SIGnatures for efficient content-based music retrieval. The signature is computed as follows: (a) each music file is split into a set of (overlapping) segments; (b) similar segments are mapped into one bucket; the number of buckets corresponds to the number of dimensions; (c) for each music file, the number of its segments that mapped to a bucket determines the key value in that dimension.

Most index structures for multimedia are only able to provide an initial filtering and return a set of candidate answers that must be further examined. For MUSIG, we want to design a scoring function that permits a ranked answer set to be generated directly based only on the signatures.