A phylogenetic analysis of near-duplicate audio tracks
We present a content-based system for the analysis of near-duplicate audio tracks. The objective is to infer the structure of modifications, represented as trees, underneath a pool of near-duplicates, possibly specifying the operations the tracks have gone through. A pilot study was carried out for a set of plausible processing operators, including trim, fade and perceptual audio coding, generating near-duplicates from an original audio track. The proposed method measures the similarity between pairs of near-duplicates and reconstructs a tree representing the causal dependencies in the analyzed pool. Experimental results demonstrate that the structure of the tree can be successfully recovered, also in the challenging case in which some pieces of information are missing, i.e., when only a subset of near-duplicate tracks is available.