Operating Sound Parameters Using Markov Model and Bayesian Filters in Automated Music Performance

Fumito Hashimoto, and Motoki Miura

Proceedings of the International Conference on New Interfaces for Musical Expression

Abstract:

In recent years, there has been an increase in the number of artists who make use of automated music performances in their music and live concerts. Automated music performance is a form of music production using programmed musical notes. Some artists who introduce automated music performance operate parameters of the sound in their performance for production of their music. In this paper, we focus on the music production aspects and describe a method that realizes operation of the sound parameters via computer. Further, in this study, the probability distribution of the action (i.e., variation of parameters) is obtained within the music, using Bayesian filters. The probability distribution of each piece of music is transformed by passing through a Markov model. After the probability distribution is obtained, sound parameters can be automatically controlled. We have developed a system to reproduce the musical expressions of humans and confirmed the possibilities of our method.

Citation:

Fumito Hashimoto, and Motoki Miura. 2014. Operating Sound Parameters Using Markov Model and Bayesian Filters in Automated Music Performance. Proceedings of the International Conference on New Interfaces for Musical Expression. DOI: 10.5281/zenodo.1178788

BibTeX Entry:

  @inproceedings{fhashimoto2014,
 abstract = {In recent years, there has been an increase in the number of artists who make use of automated music performances in their music and live concerts. Automated music performance is a form of music production using programmed musical notes. Some artists who introduce automated music performance operate parameters of the sound in their performance for production of their music. In this paper, we focus on the music production aspects and describe a method that realizes operation of the sound parameters via computer. Further, in this study, the probability distribution of the action (i.e., variation of parameters) is obtained within the music, using Bayesian filters. The probability distribution of each piece of music is transformed by passing through a Markov model. After the probability distribution is obtained, sound parameters can be automatically controlled. We have developed a system to reproduce the musical expressions of humans and confirmed the possibilities of our method.},
 address = {London, United Kingdom},
 author = {Fumito Hashimoto and Motoki Miura},
 booktitle = {Proceedings of the International Conference on New Interfaces for Musical Expression},
 doi = {10.5281/zenodo.1178788},
 issn = {2220-4806},
 month = {June},
 pages = {347--350},
 publisher = {Goldsmiths, University of London},
 title = {Operating Sound Parameters Using {Markov} Model and {Bayes}ian Filters in Automated Music Performance},
 url = {http://www.nime.org/proceedings/2014/nime2014_380.pdf},
 year = {2014}
}