Using Long-Term Structure to Retrieve Music: Representation and Matching
Jean‐Julien Aucouturier, Mark B. Sandler · 2001
We present a measure of the similarity of the long-term structure of musical pieces. The system deals with raw polyphonic data. Through unsupervised learning, we generate an abstract representation of music - the "texture score". This "texture score" can be matched to other similar scores using a generalized edit distance, in order to assess structural similarity. We notably apply this algorithm to the retrieval of different interpretations of the same song within a music database.