The research dataset is consisted of first 110 music score manuscripts of a hands-on songbook for singing reference. On the other hand, some of musical glyphs, for instances ties and Volta brackets, are common for each other. The note length (duration) of note head and flag is switched to the numbers of ‘-’, ‘.’, and ‘_’ related to note digits (see red circles in Figure 1). To name a few of the differences for pitch, the note head position relative to the staffs is substituted by numbers and the octave ‘.’ under or above digit (see blue box in Figure 1) the variety of rest notation is simplified by combination of note length glyphs and digit ‘0’. The major differences between the staff notation and the numbered musical notation are the types of musical glyphs, for example the representative staves and digits, respectively. The ecosystem is comprised of dataset, evaluation metrics, groundtruth, OMR processing engines. The authors develop the processing engines and build the whole ecosystem of Optical Music Recognition (OMR) and perform experiments. The research focuses on the sheet music written in the notation. For example, the numbered music notation (Huang, 2008), named as ‘jiănpῠ’ in pinyin for Mandarin, is well accepted in Asian. Nonetheless the notation is the most popular notation worldwide, other musical notations exist and are used in daily life. Music notation is the most important media for encoding music to play and read, therefore many classical master pieces encoded in the staff notation, conventional western music notation (CWMN) (Rastall, 1983), are alive for hundreds of years.

Numbered musical notation