Retargeting Expressive Musical Style from Classical Music Recordings Using a Support Vector Machine

Lui S, Horner A, So C. Retargeting Expressive Musical Style from Classical Music Recordings Using a Support Vector Machine. J Audio Eng Soc. 2010;58(12):1032-1044. Available from: https://aes.org/publications/elibrary-page/?id=15744

@article{Lui2010_15744,
  author = {Lui, Simon and Horner, Andrew and So, Clifford},
  title = {{Retargeting Expressive Musical Style from Classical Music Recordings Using a Support Vector Machine}},
  journal = {Journal of the Audio Engineering Society},
  volume = {58},
  number = {12},
  pages = {1032--1044},
  year = {2010},
  month = dec,
  publisher = {Audio Engineering Society},
  url = {https://aes.org/publications/elibrary-page/?id=15744}
}

TY  - JOUR
TI  - Retargeting Expressive Musical Style from Classical Music Recordings Using a Support Vector Machine
AU  - Lui, Simon
AU  - Horner, Andrew
AU  - So, Clifford
T2  - Journal of the Audio Engineering Society
J2  - J. Audio Eng. Soc.
VL  - 58
IS  - 12
SP  - 1032
EP  - 1044
PY  - 2010
DA  - 2010/12/06
UR  - https://aes.org/publications/elibrary-page/?id=15744
PB  - Audio Engineering Society
LA  - en
AB  - A method for transferring the expressive musical nuances of real recordings to a MIDI synthesized version was successfully demonstrated. Three features (dynamics, tempo, and articulation) were extracted from the recordings and then applied to the MIDI note list in order to reproduce the performer’s style. Subjective results showed that the retargeted music is very natural and sounds similar to the original performance. Statistical tests confirmed that the output correlated with the original better than with other sources. The method can successfully distinguish among different styles. A variety of applications can use this approach.
ER  -