A comparison of melodic segmentation techniques for music information retrieval

Authors:
Giovanna Neve;Nicola Orio
Affiliations:
Department of Information Engineering, University of Padova, Padova, Italy;Department of Information Engineering, University of Padova, Padova, Italy
Venue:
ECDL'05 Proceedings of the 9th European conference on Research and Advanced Technology for Digital Libraries
Year:
2005

Citing 6
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Abstract

The scientific research on accessing and retrieval of music documents is becoming increasingly active, including the analysis of suitable features for content description or the development of algorithms to match relevant documents with queries. One of the challenges in this area is the possibility to extend textual retrieval techniques to music language. Music lacks of explicit separators between its lexical units, thus they have to be automatically extracted. This paper presents an overview of different approaches to melody segmentation aimed at extracting music lexical units. A comparison of different approaches is presented, showing their impact on indexes size and on retrieval effectiveness.