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Optical Music Recognition State of the Art and Major Challenges

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Document pages: 10 pages

Abstract: Optical Music Recognition (OMR) is concerned with transcribing sheet musicinto a machine-readable format. The transcribed copy should allow musicians tocompose, play and edit music by taking a picture of a music sheet. Completetranscription of sheet music would also enable more efficient archival. OMRfacilitates examining sheet music statistically or searching for patterns ofnotations, thus helping use cases in digital musicology too. Recently, therehas been a shift in OMR from using conventional computer vision techniquestowards a deep learning approach. In this paper, we review relevant works inOMR, including fundamental methods and significant outcomes, and highlightdifferent stages of the OMR pipeline. These stages often lack standard inputand output representation and standardised evaluation. Therefore, comparingdifferent approaches and evaluating the impact of different processing methodscan become rather complex. This paper provides recommendations for future work,addressing some of the highlighted issues and represents a position infurthering this important field of research.

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