@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}
}