Music similarity: Concepts, Cognition and Computation: Editorial

TY - CHAP

T1 - Music similarity: Concepts, Cognition and Computation: Editorial

AU - Volk, Anja

AU - Chew, Elaine

AU - Margulis, Elizabeth

AU - Anagnostopoulou, Christina

PY - 2016/9/29

Y1 - 2016/9/29

N2 - Similarity is fundamental to our experience of the world (Goldstone & Son, Citation2005), and to our experience of music in particular. Accordingly, modelling music similarity is crucial for researching musical structures and cognitive processes involved in the human engagement with music within the areas of Musicology, Music Theory and Music Cognition. Moreover, the computational modelling of music similarity has become a crucial need for music research, industry and consumers over the last few decades. The dramatic increase in the digitization of music calls for the development of computational methods in Music Information Retrieval (MIR), such as content-based querying and retrieval, automatic music classification, music recommendation and digital rights management. Music similarity is a fundamental topic involved in these different aspects of music information processing. Modelling similarity has become a major challenge in various areas of Computer Science, such as in Multimedia Retrieval, Data Mining and Bioinformatics. The importance of domain specific similarity functions to be employed in search engines has been stressed (Skopal & Bustos, Citation2011). In the domain of music, similarity is a highly context-dependent notion and poses serious challenges for computational modelling. At the same time, the need for computing tools to study music similarity is crucial for music scientists, who study similarity relations in the listening process, in composition and improvisation, and through the analysis of musical scores and performances. ...

AB - Similarity is fundamental to our experience of the world (Goldstone & Son, Citation2005), and to our experience of music in particular. Accordingly, modelling music similarity is crucial for researching musical structures and cognitive processes involved in the human engagement with music within the areas of Musicology, Music Theory and Music Cognition. Moreover, the computational modelling of music similarity has become a crucial need for music research, industry and consumers over the last few decades. The dramatic increase in the digitization of music calls for the development of computational methods in Music Information Retrieval (MIR), such as content-based querying and retrieval, automatic music classification, music recommendation and digital rights management. Music similarity is a fundamental topic involved in these different aspects of music information processing. Modelling similarity has become a major challenge in various areas of Computer Science, such as in Multimedia Retrieval, Data Mining and Bioinformatics. The importance of domain specific similarity functions to be employed in search engines has been stressed (Skopal & Bustos, Citation2011). In the domain of music, similarity is a highly context-dependent notion and poses serious challenges for computational modelling. At the same time, the need for computing tools to study music similarity is crucial for music scientists, who study similarity relations in the listening process, in composition and improvisation, and through the analysis of musical scores and performances. ...

KW - music similarity

KW - music information research

KW - Computational models

U2 - 10.1080/09298215.2016.1232412

DO - 10.1080/09298215.2016.1232412

M3 - Foreword/postscript

SN - 0929-8215

VL - 45

T3 - Journal of New Music Research

SP - 207

EP - 209

BT - Music Similarity: Concepts, Cognition and Computation

PB - Taylor Francis

T2 - Music Similarity: Concepts, Cognition and Computation

Y2 - 19 January 2015 through 23 January 2015

ER -