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In this paper, we developed our own software that can analyze piano performance by using short-time Fourier transform, non-negative matrix decomposition, and root mean square. Additionally, we provided results that reflected the characteristics and signal analysis of various performers for the reliability of the developed software. The software was coded through Python, and it actively utilized Fourier transform to enable precise determination of the information needed to perform a performer's music, such as touch power, speed, and pedals. In conclusion, it shows the possibility that musical flow and waveform analysis can be visually interpreted in a variety of ways. Based on this, we were able to derive an additional approach suitable for designing the system to seamlessly connect hearing and vision.
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Jekal et al. (2025) studied this question.
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