On the suitability of state-of-the-art music information retrieval methods for analyzing, categorizing and accessing non-Western and ethnic music collections

2010 ◽  
Vol 90 (4) ◽  
pp. 1032-1048 ◽  
Author(s):  
Thomas Lidy ◽  
Carlos N. Silla ◽  
Olmo Cornelis ◽  
Fabien Gouyon ◽  
Andreas Rauber ◽  
...  
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.


2016 ◽  
Vol 40 (2) ◽  
pp. 70-83 ◽  
Author(s):  
Valerio Velardo ◽  
Mauro Vallati ◽  
Steven Jan

Fostered by the introduction of the Music Information Retrieval Evaluation Exchange (MIREX) competition, the number of systems that calculate symbolic melodic similarity has recently increased considerably. To understand the state of the art, we provide a comparative analysis of existing algorithms. The analysis is based on eight criteria that help to characterize the systems, highlighting strengths and weaknesses. We also propose a taxonomy that classifies algorithms based on their approach. Both taxonomy and criteria are fruitfully exploited to provide input for new, forthcoming research in the area.


2017 ◽  
Vol 20 (3-4) ◽  
pp. 168-183
Author(s):  
Sharon Webb ◽  
Chris Kiefer ◽  
Ben Jackson ◽  
James Baker ◽  
Alice Eldridge

2010 ◽  
Vol 90 (4) ◽  
pp. 1008-1031 ◽  
Author(s):  
Olmo Cornelis ◽  
Micheline Lesaffre ◽  
Dirk Moelants ◽  
Marc Leman

Author(s):  
Amit Rege ◽  
Ravi Sindal

An important task in music information retrieval of Indian art music is the recognition of the larger musicological frameworks, called ragas, on which the performances are based. Ragas are characterized by prominent musical notes, motifs, general sequences of notes used and embellishments improvised by the performers. In this work we propose a convolutional neural network-based model to work on the mel-spectrograms for classication of steady note regions and note transition regions in vocal melodies which can be used for finding prominent musical notes. It is demonstrated that, good classification accuracy is obtained using the proposed model.


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