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Reseach Article

A Novel System for Music Learning using Low Complexity Algorithms

by Amr Hesham, Ann Nosseir, Omar H. Karam
International Journal of Applied Information Systems
Foundation of Computer Science (FCS), NY, USA
Volume 6 - Number 4
Year of Publication: 2013
Authors: Amr Hesham, Ann Nosseir, Omar H. Karam
10.5120/ijais13-451042

Amr Hesham, Ann Nosseir, Omar H. Karam . A Novel System for Music Learning using Low Complexity Algorithms. International Journal of Applied Information Systems. 6, 4 ( October 2013), 22-29. DOI=10.5120/ijais13-451042

@article{ 10.5120/ijais13-451042,
author = { Amr Hesham, Ann Nosseir, Omar H. Karam },
title = { A Novel System for Music Learning using Low Complexity Algorithms },
journal = { International Journal of Applied Information Systems },
issue_date = { October 2013 },
volume = { 6 },
number = { 4 },
month = { October },
year = { 2013 },
issn = { 2249-0868 },
pages = { 22-29 },
numpages = {9},
url = { https://www.ijais.org/archives/volume6/number4/541-1042/ },
doi = { 10.5120/ijais13-451042 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2023-07-05T18:52:33.755163+05:30
%A Amr Hesham
%A Ann Nosseir
%A Omar H. Karam
%T A Novel System for Music Learning using Low Complexity Algorithms
%J International Journal of Applied Information Systems
%@ 2249-0868
%V 6
%N 4
%P 22-29
%D 2013
%I Foundation of Computer Science (FCS), NY, USA
Abstract

This paper introduces a music learning system that uses new low complexity algorithms and aims to solve the four most common problems faced by self-learning beginner pianists: reading music sheets, playing fast tempo music pieces, verifying the key of a music piece, and finally evaluating their own performances. In order to achieve these aims, the system proposes a monophonic automatic music transcription system capable of detecting notes in the range from G2 to G6. It uses an autocorrelation algorithm along with a binary search based algorithm in order to map the detected frequencies of the individual notes of a musical piece to the nearest musical frequencies. To enable playing fast music, the system uses a MIDI player equipped with a virtual piano as well as section looping and speed manipulation functionalities to enable the user to start learning a musical piece slowly and build up speed. Furthermore, it applies the Krumhansl-Schmuckler key-finding algorithm along with the correlation algorithm to identify the key of a musical piece. A musical performance evaluation algorithm is also introduced which compares the original performance with that of the learner's producing a quantitative similarity measure between the two. The experimental evaluation shows that the system is capable of detecting notes in the range from G2 to G6 with an accuracy of 88. 7% in addition to identifying the key of a musical piece with an accuracy of 97. 1%.

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Index Terms

Computer Science
Information Sciences

Keywords

Music learning automatic music transcription key finding monophonic music