Identification of cover songs using information theoretic measures of similarity

We consider techniques for cover song detection, based on information theoretic notions of compressibility. We propose methods for computing the normalised compression distance (NCD), while accounting for correlation between time series. Secondly, we describe methods based on cross-prediction for estimating compressibility between sequences of continuous-valued features. Using the latter approach, we view the NCD as a statistic of the prediction error. We evaluate the proposed approaches using a data set consisting of 300 Jazz songs. Quantified in terms of mean average precision, the proposed continuous-valued approach outperforms considered quantisation-based approaches.