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Monophonic Piano Music Transcription
This paper proposes a method for computational monophonic piano music transcription, which detects the pitches of piano music and thus to identify the corresponding musical notations. This computational music transcription method consists of two main algorithms, which are Onset Detection Algorithm and Pitch Detection Algorithm. The Onset Detection Algorithm involves sound wave filtering and sound wave segmentation. And the Pitch Detection Algorithm involves period determination, frequency computation and musical notation identification. These proposed algorithms adopt time-domain method and they are built based on the observation of characteristics of piano sound signal. The program is fast and simple to use, and able to output result with 88% accuracy. However, this music transcription method is limited to specific sound input only, that is the monophonic piano music with slow or average speed up to 120 crotchet beats per minute. It is because the performances of the algorithms are dependent on the threshold values set in the program. Therefore, further investigation and research have to be carried out in order to improve the performance of the program.
Automatic Music Transcription, Onset Detection Algorithm, Pitch Detection Algorithm.
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