loading
Papers Papers/2022 Papers Papers/2022

Research.Publish.Connect.

Paper

Paper Unlock

Authors: M. Cicconet ; P. Carvalho ; L. Velho and M. Gattass

Affiliation: Vision and Graphics Laboratory at IMPA and Computer Science Department at PUC-Rio, Brazil

Keyword(s): Guitar Chord Identification, Chord Detection, Pitch Class Profile, Chroma Vector.

Related Ontology Subjects/Areas/Topics: Artificial Intelligence ; Biomedical Engineering ; Biomedical Signal Processing ; Data Manipulation ; Health Engineering and Technology Applications ; Human-Computer Interaction ; Methodologies and Methods ; Neurocomputing ; Neurotechnology, Electronics and Informatics ; Pattern Recognition ; Physiological Computing Systems ; Sensor Networks ; Soft Computing

Abstract: We propose a video-based method for real-time guitar chord identification which is analogous to the state-of-the-art audio-based method. While the method based on audio data uses the Pitch Class Profile feature and supervised Machine Learning techniques to ``teach'' the machine about the chord ``shape'', we use as feature the approximated positions of fingertips in the guitar fretboard (what we call Visual Pitch Class Profile), captured using especial hardware. We show that visual- and audio-based methods have similar classification performance, but the former outperforms the latter with respect to the immunity to noise caused by strumming.

CC BY-NC-ND 4.0

Sign In Guest: Register as new SciTePress user now for free.

Sign In SciTePress user: please login.

PDF ImageMy Papers

You are not signed in, therefore limits apply to your IP address 44.220.44.148

In the current month:
Recent papers: 100 available of 100 total
2+ years older papers: 200 available of 200 total

Paper citation in several formats:
Cicconet, M.; Carvalho, P.; Velho, L. and Gattass, M. (2010). VISUAL PITCH CLASS PROFILE - A Video-based Method for Real-time Guitar Chord Identification. In Proceedings of the International Conference on Computer Vision Theory and Applications (VISIGRAPP 2010) - Volume 2: VISAPP; ISBN 978-989-674-029-0; ISSN 2184-4321, SciTePress, pages 487-490. DOI: 10.5220/0002824904870490

@conference{visapp10,
author={M. Cicconet. and P. Carvalho. and L. Velho. and M. Gattass.},
title={VISUAL PITCH CLASS PROFILE - A Video-based Method for Real-time Guitar Chord Identification},
booktitle={Proceedings of the International Conference on Computer Vision Theory and Applications (VISIGRAPP 2010) - Volume 2: VISAPP},
year={2010},
pages={487-490},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0002824904870490},
isbn={978-989-674-029-0},
issn={2184-4321},
}

TY - CONF

JO - Proceedings of the International Conference on Computer Vision Theory and Applications (VISIGRAPP 2010) - Volume 2: VISAPP
TI - VISUAL PITCH CLASS PROFILE - A Video-based Method for Real-time Guitar Chord Identification
SN - 978-989-674-029-0
IS - 2184-4321
AU - Cicconet, M.
AU - Carvalho, P.
AU - Velho, L.
AU - Gattass, M.
PY - 2010
SP - 487
EP - 490
DO - 10.5220/0002824904870490
PB - SciTePress