Violin Sound Computer Classification Based on Expert Knowledge

Robak A, Lukasik E. Violin Sound Computer Classification Based on Expert Knowledge. In: AES Convention 134. Audio Engineering Society; 2013. Paper 8815. Available from: https://aes.org/publications/elibrary-page/?id=16716

@inproceedings{Robak2013_16716,
  author = {Robak, Adam and Lukasik, Ewa},
  title = {{Violin Sound Computer Classification Based on Expert Knowledge}},
  booktitle = {AES Convention 134},
  note = {Paper 8815},
  year = {2013},
  month = may,
  publisher = {Audio Engineering Society},
  url = {https://aes.org/publications/elibrary-page/?id=16716}
}

TY  - CPAPER
TI  - Violin Sound Computer Classification Based on Expert Knowledge
AU  - Robak, Adam
AU  - Lukasik, Ewa
T2  - AES Convention 134
M1  - Paper 8815
PY  - 2013
DA  - 2013/05/06
UR  - https://aes.org/publications/elibrary-page/?id=16716
PB  - Audio Engineering Society
LA  - en
AB  - The paper presents results of the analysis of violins recorded during the final stage of the international violin-makers competition held in Poznan in 2011. In the quest for attributes that are both efficient for machine learning and interpretable for human experts we referred to the research of violin acousticians: Duennwald, Buen, and Fritz and calculated violin sound power in frequency bands recommended by these researchers. The resulting features, obtained for the averaged spectra of the musical pieces played at the competition, were used for clustering and classification experiments. Results are discussed, and a notable experiment is presented where the classifier assigns each analyzed violin to an instrument from the precedent violinmakers’ competition (2001) and compares their ranking.
ER  -