A Comparative Analysis of Music Similarity Measures in Music Information Retrieval Systems


Kuldeep Gurjar, Yang-Sae Moon, Journal of Information Processing Systems Vol. 14, No. 1, pp. 32-55, Jan. 2018  

10.3745/JIPS.04.0054
Keywords: Content-Based Music Retrieval, MIR System, Music Information Retrieval Survey, Music Similarity Measures
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Abstract

The digitization of music has seen a considerable increase in audience size from a few localized listeners to a wider range of global listeners. At the same time, the digitization brings the challenge of smoothly retrieving music from large databases. To deal with this challenge, many systems which support the smooth retrieval of musical data have been developed. At the computational level, a query music piece is compared with the rest of the music pieces in the database. These systems, music information retrieval (MIR systems), work for various applications such as general music retrieval, plagiarism detection, music recommendation, and musicology. This paper mainly addresses two parts of the MIR research area. First, it presents a general overview of MIR, which will examine the history of MIR, the functionality of MIR, application areas of MIR, and the components of MIR. Second, we will investigate music similarity measurement methods, where we provide a comparative analysis of state of the art methods. The scope of this paper focuses on comparative analysis of the accuracy and efficiency of a few key MIR systems. These analyses help in understanding the current and future challenges associated with the field of MIR systems and music similarity measures


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Cite this article
[APA Style]
Kuldeep Gurjar and Yang-Sae Moon (2018). A Comparative Analysis of Music Similarity Measures in Music Information Retrieval Systems. Journal of Information Processing Systems, 14(1), 32-55. DOI: 10.3745/JIPS.04.0054.

[IEEE Style]
K. Gurjar and Y. Moon, "A Comparative Analysis of Music Similarity Measures in Music Information Retrieval Systems," Journal of Information Processing Systems, vol. 14, no. 1, pp. 32-55, 2018. DOI: 10.3745/JIPS.04.0054.

[ACM Style]
Kuldeep Gurjar and Yang-Sae Moon. 2018. A Comparative Analysis of Music Similarity Measures in Music Information Retrieval Systems. Journal of Information Processing Systems, 14, 1, (2018), 32-55. DOI: 10.3745/JIPS.04.0054.