The Realisation of Online Music Services through Intelligent Computing

Author(s):  
Panagiotis Zervas ◽  
Chrisoula Alexandraki

This chapter presents an extensive, although non-exhaustive, study on existing Online Music Services (OMSs), which aims at identifying two principal characteristics: (1) the functionalities and interaction capabilities offered to their end-users; and (2) the tools of computational intelligence employed so as to enable these functionalities. The study is predominantly motivated by the ever-growing impact of Music Information Retrieval (MIR) research on the music industry, as new approaches for knowledge acquisition are rapidly integrated in existing online services targeting music consumers, musicians, as well as the music industry. Since MIR is inherently addressing user needs in music aggregation and distribution, the first part of the chapter is dedicated to illustrating user functionalities and accordingly classifying existing OMSs. The second part of the chapter focuses on musical semantics, different methods for harvesting them, and approaches for exploiting them in existing OMSs. Finally, the chapter attempts to foresee functionalities of future OMSs enabled by forthcoming MIR achievements.

Heliyon ◽  
2021 ◽  
Vol 7 (2) ◽  
pp. e06257
Author(s):  
Ennio Idrobo-Ávila ◽  
Humberto Loaiza-Correa ◽  
Rubiel Vargas-Cañas ◽  
Flavio Muñoz-Bolaños ◽  
Leon van Noorden

2020 ◽  
pp. 102986492097216
Author(s):  
Gaelen Thomas Dickson ◽  
Emery Schubert

Background: Music is thought to be beneficial as a sleep aid. However, little research has explicitly investigated the specific characteristics of music that aid sleep and some researchers assume that music described as generically sedative (slow, with low rhythmic activity) is necessarily conducive to sleep, without directly interrogating this assumption. This study aimed to ascertain the features of music that aid sleep. Method: As part of an online survey, 161 students reported the pieces of music they had used to aid sleep, successfully or unsuccessfully. The participants reported 167 pieces, some more often than others. Nine features of the pieces were analyzed using a combination of music information retrieval methods and aural analysis. Results: Of the pieces reported by participants, 78% were successful in aiding sleep. The features they had in common were that (a) their main frequency register was middle range frequencies; (b) their tempo was medium; (c) their articulation was legato; (d) they were in the major mode, and (e) lyrics were present. They differed from pieces that were unsuccessful in aiding sleep in that (a) their main frequency register was lower; (b) their articulation was legato, and (c) they excluded high rhythmic activity. Conclusion: Music that aids sleep is not necessarily sedative music, as defined in the literature, but some features of sedative music are associated with aiding sleep. In the present study, we identified the specific features of music that were reported to have been successful and unsuccessful in aiding sleep. The identification of these features has important implications for the selection of pieces of music used in research on sleep.


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