Music identification by Leadsheets

Abstract

Most experimental research on content-based automatic recognition and identification of musical documents is founded on statistical distribution of timbre or simple retrieval mechanisms like comparison of melodic segments. Therefore often a vast number of relevant and irrelevant hits including multiple appearances of the same documents are returned or the actual document can’t be revealed at all. To improve this situation we propose a model for recognition of music that enables identification and comparison of musical documents without dependence on their actual instantiation. The resulting structures enclose musical meaning and can be used for estimation of identity and semantic relationship between musical documents.