Optical Music Recognition for Numbered Music Notation with Multimodal Reconstruction

2013 ◽  
Vol 479-480 ◽  
pp. 943-947
Author(s):  
Fu Hai Frank Wu ◽  
Jyh Shing Roger Jang
Keyword(s):  
Information Retrieval ◽  
Small Group ◽  
Music Information Retrieval ◽  
Music Notation ◽  
Modern Music ◽  
Notation System ◽  
Optical Music Recognition ◽  
Neighborhood Relationship ◽  
Music Recognition ◽  
Music Information

Optical music recognition (OMR) is attracted a lot attention on different music notation system which could be so focused on Back’s C-Clefs; in contrast, it could handle complete modern music symbols. One of notation system, numbered music notation, which is literally call “simplified notation”, is popular in many Asia countries. There is a traditional Chinese hymnbook, which usually used in small group of worship, in which one page has several hymns. We propose algorithms for the recognition of those notations in camera images of the hymn, which could effectively identify score zone and lyric zone, segment notation image, classify music notation, and reconstruct scores from classified notation by their coordinates and neighborhood relationship. Those algorithms comprise the preliminary demo system by which we provide a solution for music information retrieval and reconstruction.

scholarly journals Can the application of certain music information retrieval methods contribute to the machine learning classification of electrocardiographic signals?

Heliyon ◽  
2021 ◽  
Vol 7 (2) ◽  
pp. e06257
Author(s):  
Ennio Idrobo-Ávila ◽  
Humberto Loaiza-Correa ◽  
Rubiel Vargas-Cañas ◽  
Flavio Muñoz-Bolaños ◽  
Leon van Noorden
Keyword(s):  
Machine Learning ◽  
Information Retrieval ◽  
Music Information Retrieval ◽  
Machine Learning Classification ◽  
Information Retrieval Methods ◽  
Music Information

Musical Features that Aid Sleep

2020 ◽  
pp. 102986492097216
Author(s):  
Gaelen Thomas Dickson ◽  
Emery Schubert
Keyword(s):  
Information Retrieval ◽  
Online Survey ◽  
Music Information Retrieval ◽  
Rhythmic Activity ◽  
Main Frequency ◽  
Middle Range ◽  
Major Mode ◽  
Information Retrieval Methods ◽  
Music Information ◽  
Selection Of

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.

A Scalable Peer-to-Peer System for Music Information Retrieval

2004 ◽  
Vol 28 (2) ◽  
pp. 24-33 ◽  
Author(s):  
George Tzanetakis ◽  
Jun Gao ◽  
Peter Steenkiste
Keyword(s):  
Information Retrieval ◽  
Music Information Retrieval ◽  
Peer To Peer ◽  
Music Information
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