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A. Robak, and E. Lukasik, "Violin Sound Computer Classification Based on Expert Knowledge," Paper 8815, (2013 May.). doi: A. Robak, and E. Lukasik, "Violin Sound Computer Classification Based on Expert Knowledge," Paper 8815, (2013 May.). doi:
Abstract: 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.

@article{robak2013violin,
author={robak, adam and lukasik, ewa},
journal={journal of the audio engineering society},
title={violin sound computer classification based on expert knowledge},
year={2013},
volume={},
number={},
pages={},
doi={},
month={may},} @article{robak2013violin,
author={robak, adam and lukasik, ewa},
journal={journal of the audio engineering society},
title={violin sound computer classification based on expert knowledge},
year={2013},
volume={},
number={},
pages={},
doi={},
month={may},
abstract={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.},}

TY - paper
TI - Violin Sound Computer Classification Based on Expert Knowledge
SP - EP -
AU - Robak, Adam
AU - Lukasik, Ewa
PY - 2013
JO - Journal of the Audio Engineering Society
IS -
VO -
VL -
Y1 - May 2013 TY - paper
TI - Violin Sound Computer Classification Based on Expert Knowledge
SP - EP -
AU - Robak, Adam
AU - Lukasik, Ewa
PY - 2013
JO - Journal of the Audio Engineering Society
IS -
VO -
VL -
Y1 - May 2013
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.