TIIS (한국인터넷정보학회)
Current Result Document :
| 한글제목(Korean Title) |
Application and Research of Monte Carlo Sampling Algorithm in Music Generation |
| 영문제목(English Title) |
Application and Research of Monte Carlo Sampling Algorithm in Music Generation |
| 저자(Author) |
Ying Zhu
Caixia Liu
Yiming Zhang
Wei You
Jun MIN
Lei WANG
Junwei PANG
Huihui HAN
Dongyang Li
Maoqing ZHANG
Yantai HUANG
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| 원문수록처(Citation) |
VOL 16 NO. 10 PP. 3355 ~ 3372 (2022. 10) |
한글내용
(Korean Abstract) |
|
영문내용
(English Abstract) |
Composing music is an inspired yet challenging task, in that the process involves many considerations such as assigning pitches, determining rhythm, and arranging accompaniment. Algorithmic composition aims to develop algorithms for music composition. Recently, algorithmic composition using artificial intelligence technologies received considerable attention. In particular, computational intelligence is widely used and achieves promising results in the creation of music. This paper attempts to provide a survey on the music generation based on the Monte Carlo (MC) algorithm. First, transform the MIDI music format files to digital data. Among these data, use the logistic fitting method to fit the time series, obtain the time distribution regular pattern. Except for time series, the converted data also includes duration, pitch, and velocity. Second, using MC simulation to deal with them summed up their distribution law respectively. The two main control parameters are the value of discrete sampling and standard deviation. Processing the above parameters and converting the data to MIDI file, then compared with the output generated by LSTM neural network, evaluate the music comprehensively. |
| 키워드(Keyword) |
5G
5G Core Network
trust model
time decay
punishment mechanism
trust transmit
Music generation
MIDI
Monte Carlo
Data convert
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| 파일첨부 |
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