Paper Info
Title
Music similarity: improvements of edit-based algorithms by considering music theory
Abstract
Estimating the symbolic music similarity is one of the major open problems in the music information retrieval research domain. Existing systems consider sequences of notes characterized by pitches and durations. Similarity estimation is mainly based on variations of pitches and durations and does not consider any other musical elements. However, musical elements such as tonality or rhythm are particularly important in the perception of music. In this paper we propose to investigate some algorithmic improvements that allow edit-based systems to take into account important musical elements: tonality, passing notes, strong and weak beats. These elements are illustrated with a few monophonic musical examples which lead to important errors in usual systems. First experiments with these examples show that the improvements induced are significant. Furthermore, experimental results obtained with the MIREX 2005 database are very good. All the results are thus very promising since they confirm that considering musical information improves the accuracy of music retrieval systems.
Year
DOI
Venue
2007
10.1145/1290082.1290103
Multimedia Information Retrieval
Keywords
Field
DocType
important error,monophonic musical example,symbolic music similarity,music information retrieval research,musical element,account important musical element,musical information,edit-based algorithm,music retrieval system,music theory,algorithmic improvement,similarity estimation,information retrieval
Music information retrieval,Music theory,Computer science,Musical,Speech recognition,Pop music automation,Perception,Rhythm,Tonality
Conference
Citations 
PageRank 
References 
4
0.41
14
Authors
3
Name
Order
Citations
PageRank
Matthias Robine17413.06
Pierre Hanna211020.53
Pascal Ferraro37711.54