Miguel Molina-Solana

Music performance education is a challenging domain for Artificial Intelligence due to the inherent complexity of music, an activity with no clear goals and no comprehensive set of well-defined methods for success. It involves complementary aspects from other disciplines such as psychology and acoustics; and it also requires creativity and manual skills. In this paper, we present an application of machine learning to music performance training. Our devised system is able to discover the similarities and differences between a given performance and those from other musicians. Such a system is useful to music students when learning how to perform a music piece.

@inproceedings{caepia2018_violin,
  title = {A software tool for categorizing violin student renditions by comparison},
  author = {Delgado, Miguel and Fajardo, Waldo and Molina-Solana, Miguel},
  booktitle = {Proc. CAEPIA 2018},
  year = {2018},
  address = {Granada, Spain},
  month = oct,
  timestamp = {125},
  doi = {10.1007/978-3-030-00374-6_31},
  url = {http://caepia18.aepia.org}
}