Open AccessMonophonic Musical Instrument Sound Classification Using Impulse Response Modeling
Author(s) -
Rutuja S Kothe
Publication year - 2021
Publication title -
türk bilgisayar ve matematik eğitimi dergisi
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.218
H-Index - 3
ISSN - 1309-4653
DOI - 10.17762/turcomat.v12i5.2155
Subject(s) - musical instrument , impulse response , classifier (uml) , musical , impulse (physics) , computer science , mel frequency cepstrum , speech recognition , time domain , pattern recognition (psychology) , artificial intelligence , feature extraction , acoustics , mathematics , computer vision , art , quantum mechanics , visual arts , mathematical analysis , physics
The field of music has promising commercial and social applications. Hence it has attracted the attention of researchers, engineers, sociologists and health care peoples. Therefore this particular research area has been selected.
In this manuscript the monophonic musical classificationsystem using impulse response of the system is presented. In this research work 19 musical instruments monophonic sounds from 4 families are classified using WEKA classifier. The impulse response is of all musical instruments and families are computed in Cepstral Domain. AsImpulse response is used to model the body response of the musical instruments and helps to capture the information. It is different for different instruments. The features are extracted from impulse response and presented to WEKA Classifier.
The Musical instrument classification for individual instruments and family is verified using impulse response modeling. It is found that the impulse response is different for different instruments. It helps to easily distinguish between instrument to instrument and family to family. For individual instruments, the average classification accuracy has been obtained is 83.23% and 85.55% for family classification.