An optical music recognition system for traditional Chinese Kunqu Opera scores written in Gong-Che Notation

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This paper presents an optical music recognition (OMR) system to process the handwritten musical scores of Kunqu Opera written in Gong-Che Notation (GCN). First, it introduces the background of Kunqu Opera and GCN. Kunqu Opera is one of the oldest forms of musical activity, spanning the sixteenth to eighteenth centuries, and GCN has been the most popular notation for recording musical works in China since the seventh century. Many Kunqu Operas that use GCN are available as original manuscripts or photocopies, and transforming these versions into a machine-readable format is a pressing need. The OMR system comprises six stages: image pre-processing, segmentation, feature extraction, symbol recognition, musical semantics, and musical instrument digital interface (MIDI) representation. This paper focuses on the symbol recognition stage and obtains the musical information with Bayesian, genetic algorithm, and K-nearest neighbor classifiers. The experimental results indicate that symbol recognition for Kunqu Opera's handwritten musical scores is effective. This work will help to preserve and popularize Chinese cultural heritage and to store Kunqu Opera scores in a machine-readable format, thereby ensuring the possibility of spreading and performing original Kunqu Opera musical scores.