MUSICAL INSTRUMENT SKILL TRAINING SYSTEM USING PITCH DETECTION ALGORITHM
Music is one of the topics that is taught from an early age. However, there are several issues with music education, such as the presence of incompetent music teachers and the difficulty in obtaining interactive resources for learning music similar to private lessons. Although there are already s...
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id-itb.:821572024-07-05T22:51:08ZMUSICAL INSTRUMENT SKILL TRAINING SYSTEM USING PITCH DETECTION ALGORITHM Naufal Satriandana, Muhammad Indonesia Final Project music, pitch, pitch detection algorithm, Harmonic Product Spectrum INSTITUT TEKNOLOGI BANDUNG https://digilib.itb.ac.id/gdl/view/82157 Music is one of the topics that is taught from an early age. However, there are several issues with music education, such as the presence of incompetent music teachers and the difficulty in obtaining interactive resources for learning music similar to private lessons. Although there are already several applications available on mobile and desktop devices that can train musical instrument skills, the lack of flexibility in the content provided becomes a problem for those who want to customize their practice according to their needs. For this reason, an interactive and customizable musical instrument skill training system is needed. For a flexible system, users should have the freedom to design, modify, and play their own practice sessions as desired. The features built into the system must not only be flexible but also interactive, requiring the ability to detect the notes played by the user in real-time. For this purpose, a pitch detection algorithm which can detect the notes played by the user in real-time is utilized. This algorithm is implemented in a desktop-based application with a graphical user interface. The system uses the Harmonic Product Spectrum as the pitch detection algorithm because it is one of the simplest note detection algorithms, performs well in various conditions, and has low computational costs. The developed system can detect 131 out of 132 test cases from three different instruments, namely acoustic guitar, electric guitar, and piano, achieving a detection accuracy of 99.2%. This system has the potential to train several skills, including playing sequences of notes, memorizing notes, playing scales in a key, and training intervals and other music theories related to note relationships. text |
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Music is one of the topics that is taught from an early age. However, there are
several issues with music education, such as the presence of incompetent music
teachers and the difficulty in obtaining interactive resources for learning music
similar to private lessons. Although there are already several applications available
on mobile and desktop devices that can train musical instrument skills, the lack of
flexibility in the content provided becomes a problem for those who want to
customize their practice according to their needs. For this reason, an interactive and
customizable musical instrument skill training system is needed. For a flexible
system, users should have the freedom to design, modify, and play their own
practice sessions as desired. The features built into the system must not only be
flexible but also interactive, requiring the ability to detect the notes played by the
user in real-time. For this purpose, a pitch detection algorithm which can detect the
notes played by the user in real-time is utilized. This algorithm is implemented in a
desktop-based application with a graphical user interface. The system uses the
Harmonic Product Spectrum as the pitch detection algorithm because it is one of
the simplest note detection algorithms, performs well in various conditions, and has
low computational costs. The developed system can detect 131 out of 132 test cases
from three different instruments, namely acoustic guitar, electric guitar, and piano,
achieving a detection accuracy of 99.2%. This system has the potential to train
several skills, including playing sequences of notes, memorizing notes, playing
scales in a key, and training intervals and other music theories related to note
relationships. |
format |
Final Project |
author |
Naufal Satriandana, Muhammad |
spellingShingle |
Naufal Satriandana, Muhammad MUSICAL INSTRUMENT SKILL TRAINING SYSTEM USING PITCH DETECTION ALGORITHM |
author_facet |
Naufal Satriandana, Muhammad |
author_sort |
Naufal Satriandana, Muhammad |
title |
MUSICAL INSTRUMENT SKILL TRAINING SYSTEM USING PITCH DETECTION ALGORITHM |
title_short |
MUSICAL INSTRUMENT SKILL TRAINING SYSTEM USING PITCH DETECTION ALGORITHM |
title_full |
MUSICAL INSTRUMENT SKILL TRAINING SYSTEM USING PITCH DETECTION ALGORITHM |
title_fullStr |
MUSICAL INSTRUMENT SKILL TRAINING SYSTEM USING PITCH DETECTION ALGORITHM |
title_full_unstemmed |
MUSICAL INSTRUMENT SKILL TRAINING SYSTEM USING PITCH DETECTION ALGORITHM |
title_sort |
musical instrument skill training system using pitch detection algorithm |
url |
https://digilib.itb.ac.id/gdl/view/82157 |
_version_ |
1822997584616095744 |