Recognition of piano keyboards based on sound feature extraction
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@Article{JICS-14-178,
author = {Lun Li and Cheng Li},
title = {Recognition of piano keyboards based on sound feature extraction},
journal = {Journal of Information and Computing Science},
year = {2024},
volume = {14},
number = {3},
pages = {178--183},
abstract = {School of Computing, University of Kent, CT2 7NZ, England, UK
(Received May 10 2019, accepted June 11 2019)
The tones of piano are produced by regular periodic oscillations and different keys’ individual
inherent audio characteristics. Based on the collection of the sound wave signals and the analysis of the
frequency characteristics from different keys, this study explores the methods to effectively identify and detect
the corresponding numbers of keys. This paper will also compare and analyzed the different methods of audio
signal extraction and identification of piano keys, to find effective methods to make theoretical preparation for
further system development.
},
issn = {1746-7659},
doi = {https://doi.org/},
url = {http://global-sci.org/intro/article_detail/jics/22411.html}
}
TY - JOUR
T1 - Recognition of piano keyboards based on sound feature extraction
AU - Lun Li and Cheng Li
JO - Journal of Information and Computing Science
VL - 3
SP - 178
EP - 183
PY - 2024
DA - 2024/01
SN - 14
DO - http://doi.org/
UR - https://global-sci.org/intro/article_detail/jics/22411.html
KW - Piano key identification, sound feature extraction, Pattern Recognition, Numerical analysis
AB - School of Computing, University of Kent, CT2 7NZ, England, UK
(Received May 10 2019, accepted June 11 2019)
The tones of piano are produced by regular periodic oscillations and different keys’ individual
inherent audio characteristics. Based on the collection of the sound wave signals and the analysis of the
frequency characteristics from different keys, this study explores the methods to effectively identify and detect
the corresponding numbers of keys. This paper will also compare and analyzed the different methods of audio
signal extraction and identification of piano keys, to find effective methods to make theoretical preparation for
further system development.
Lun Li and Cheng Li. (2024). Recognition of piano keyboards based on sound feature extraction.
Journal of Information and Computing Science. 14 (3).
178-183.
doi:
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