The importance of sequences in musical similarity

This paper demonstrates the importance of temporal sequences for passage-level music information retrieval. A number of audio analysis problems are solved successfully by using models that throw away the temporal sequence data. This paper suggests that we do not have this luxury when we consider a more difficult problem: that is finding musically similar passages within a narrow range of musical styles or within a single musical piece. Our results demonstrate a significant improvement in performance for audio similarity measures using temporal sequences of features, and we show that quantizing the features to string-based representations also performs well, thus admitting efficient implementations based on string matching.