Music note position recognition in optical music recognition using convolutional neural network

被引:0
|
作者
Andrea [1 ]
Paoline [1 ]
Zahra, Amalia [1 ]
机构
[1] Bina Nusantara Univ, Dept Comp Sci, Jakarta 11480, Indonesia
关键词
optical music recognition; OMR; music; pitch recognition; deep learning; convolutional neural network; CNN; music sheet; DEEP; ART;
D O I
10.1504/IJART.2021.115764
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
Technology improvement is rapidly changing. This impacts many fields, including the music field. Technology has helped the music field to be recognised in machine understanding. This field is called optical music recognition (OMR), a computer vision enabler in music. With OMR, we can define the position and music notation in music note. We propose a deep learning and convolutional neural network (CNN) approach to recognise a music position in music note. Music note position in staff is one of the keys to achieve pitch recognition. While we have music clef, key signature, and note position in staff, we can give machines the understanding of a note pitch. This experiment can bring and broaden the experiments in recognising music pitch, which take music note image as an input and position as the output. We use our own dataset and use CNN in experiments. This note position recognition experiment achieved 80% accuracy.
引用
收藏
页码:45 / 60
页数:16
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