Study and Application of Monte Carlo Algorithm for AI-Based Music Generation
- 10.2991/978-94-6463-012-1_44How to use a DOI?
- Music Generation; Monte Carlo Method; Data Analysis; MIDI
When generating music via algorithms, it is essential to extract music characteristics and the distribution of notes. A Monte Carlo simulation framework for music generation was proposed on the premise of maintaining the authenticity of music samples. Those samples, which are stored in MIDI format, were first converted into data that can be processed by computes. To simulate music time series, we adopted Logistic regression. Except for time series, the converted data also include three parameters: duration, pitch, and velocity. We first solved the correlation coefficient matrix and standard deviation of the three parameters, and then analyzed them using Monte Carlo method and summarized their distribution patterns.
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Cite this article
TY - CONF AU - Jun Min AU - Lei Wang PY - 2022 DA - 2022/12/09 TI - Study and Application of Monte Carlo Algorithm for AI-Based Music Generation BT - Proceedings of the 2022 International Conference on Educational Innovation and Multimedia Technology (EIMT 2022) PB - Atlantis Press SP - 392 EP - 402 SN - 2667-128X UR - https://doi.org/10.2991/978-94-6463-012-1_44 DO - 10.2991/978-94-6463-012-1_44 ID - Min2022 ER -