School of Preschool Education, Guangdong Nanhua Vocational College of Industry and Commerce, Guangzhou 510510, China.
Comput Intell Neurosci. 2022 Jun 2;2022:2278683. doi: 10.1155/2022/2278683. eCollection 2022.
In the era of rapid development of computer technology, piano music notation and electronic synthesis system can be established using computer technology, and the basic laws of music score can be analyzed from the perspective of image processing, which is of a great significance in promoting piano improvement and research and development, etc. In this paper, the Beaulieu analysis method is used to analyze the piano music notation and electronic synthesis system module. For piano sheet music, sheet music recognition is the main problem in the whole system. Through the digital recognition method, the piano sheet music feature matrix is extracted to get the piano sheet music multiplication frequency points and the envelope function needs to be extracted for better electronic synthesis of piano sheet music. The envelope function can represent the relationship between piano sound intensity and time change and finally achieve the recognition of the piano score. We extract the music information from the digital score, thus converting the music information into MIDI files, reconstructing the score, and providing an audio carrier for the score transmission. The experimental results show that the system has a correct rate of 94.4% in extracting music information from piano scores, which can meet the needs of practical applications and provide a new way for music digital libraries, music education, and music theory analysis.
在计算机技术飞速发展的时代，可以利用计算机技术建立钢琴乐谱记谱法和电子合成系统，并从图像处理的角度分析音乐乐谱的基本规律，这对促进钢琴的改进和研究与开发等具有重要意义。本文采用 Beaulieu 分析法对钢琴乐谱记谱法和电子合成系统模块进行分析。对于钢琴乐谱，乐谱识别是整个系统的主要问题。通过数字识别方法，提取钢琴乐谱特征矩阵，得到钢琴乐谱的倍频点，并提取包络函数，以便更好地对钢琴乐谱进行电子合成。包络函数可以表示钢琴声音强度与时间变化的关系，最终实现乐谱的识别。我们从数字乐谱中提取音乐信息，从而将音乐信息转换为 MIDI 文件，重构乐谱，并为乐谱传输提供音频载体。实验结果表明，该系统从钢琴乐谱中提取音乐信息的准确率为 94.4%，可以满足实际应用的需要，为音乐数字图书馆、音乐教育和音乐理论分析提供了新的途径。
