Alignment of Performances with Scores Aimed at Content-Based Music Access and Retrieval

Abstract

Music digital libraries pose interesting and challenging research problems, in particular for the development of methodologies and tools for the retrieval of music documents. One difficult aspect of content- based retrieval of musical works is that only scores can be represented by a symbolic notation, while performances, which are of interest for the majority of users, allow for access based on bibliographic values only. The research work reported in this paper proposes to index and retrieve music performances through an automatic alignment of acoustic recordings with the music scores. Alignment my allow for: automatic recognition of performances, aimed at cataloging large collections of recordings; automatic tagging of performances, aimed at an easy access to long recordings. The methodology is based on the use of hidden Markov models, a powerful tool that has been successfully used in many research areas, like speech recognition and molecular biology. The approach has been tested on a collection of acoustic and synthetic performances, showing good results in the recognition and in the tagging of performances. The proposed approach can be used to increase the functionalities of a music digital library, allowing for content-based access to scores and recordings.