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J. Abeßer, C. Dittmar, and G. Schuller, "Automatic Recognition and Parametrization of Frequency Modulation Techniques in Bass Guitar Recordings," Paper 3-1, (2011 July.). doi: J. Abeßer, C. Dittmar, and G. Schuller, "Automatic Recognition and Parametrization of Frequency Modulation Techniques in Bass Guitar Recordings," Paper 3-1, (2011 July.). doi:
Abstract: In this paper, we propose a novel method to parametrize and classify different frequency modulation techniques in bass guitar recordings. A parametric spectral estimation technique is applied to refine the fundamental frequency estimates derived from an existing bass transcription algorithm. We apply a two-stage taxonomy of bass playing styles with special focus on the frequency modulation techniques slide, bending, and vibrato. An existing database of isolated note recordings is extended by approx. 900 samples to evaluate the presented algorithm. We achieve comparable classification accuracy values of 85.1% and 81.5% for classification on class-level and subclass-level. Furthermore, two potential application scenarios are outlined.

@article{abeßer2011automatic,
author={abeßer, jakob and dittmar, christian and schuller, gerald},
journal={journal of the audio engineering society},
title={automatic recognition and parametrization of frequency modulation techniques in bass guitar recordings},
year={2011},
volume={},
number={},
pages={},
doi={},
month={july},} @article{abeßer2011automatic,
author={abeßer, jakob and dittmar, christian and schuller, gerald},
journal={journal of the audio engineering society},
title={automatic recognition and parametrization of frequency modulation techniques in bass guitar recordings},
year={2011},
volume={},
number={},
pages={},
doi={},
month={july},
abstract={in this paper, we propose a novel method to parametrize and classify different frequency modulation techniques in bass guitar recordings. a parametric spectral estimation technique is applied to refine the fundamental frequency estimates derived from an existing bass transcription algorithm. we apply a two-stage taxonomy of bass playing styles with special focus on the frequency modulation techniques slide, bending, and vibrato. an existing database of isolated note recordings is extended by approx. 900 samples to evaluate the presented algorithm. we achieve comparable classification accuracy values of 85.1% and 81.5% for classification on class-level and subclass-level. furthermore, two potential application scenarios are outlined.},}

TY - paper
TI - Automatic Recognition and Parametrization of Frequency Modulation Techniques in Bass Guitar Recordings
SP - EP -
AU - Abeßer, Jakob
AU - Dittmar, Christian
AU - Schuller, Gerald
PY - 2011
JO - Journal of the Audio Engineering Society
IS -
VO -
VL -
Y1 - July 2011 TY - paper
TI - Automatic Recognition and Parametrization of Frequency Modulation Techniques in Bass Guitar Recordings
SP - EP -
AU - Abeßer, Jakob
AU - Dittmar, Christian
AU - Schuller, Gerald
PY - 2011
JO - Journal of the Audio Engineering Society
IS -
VO -
VL -
Y1 - July 2011
AB - In this paper, we propose a novel method to parametrize and classify different frequency modulation techniques in bass guitar recordings. A parametric spectral estimation technique is applied to refine the fundamental frequency estimates derived from an existing bass transcription algorithm. We apply a two-stage taxonomy of bass playing styles with special focus on the frequency modulation techniques slide, bending, and vibrato. An existing database of isolated note recordings is extended by approx. 900 samples to evaluate the presented algorithm. We achieve comparable classification accuracy values of 85.1% and 81.5% for classification on class-level and subclass-level. Furthermore, two potential application scenarios are outlined.