Using mutual proximity for novelty detection in audio music similarity
Arthur Flexer, Dominik Schnitzer · 2013
Abstract. Mutual proximity rescales distance spaces to avoid negative effects of the curse of dimensionality. It results in probabilistic estimates of the proximity of data objects. We use these probabilities directly for novelty detection, i.e. the automatic identification of unknown data not covered by training data (e.g. a new genre in genre classification). Com-paring this new approach with a distance based detection method we demonstrate improved performance on a standard music data set. 1