TY - JOUR
T1 - Arabic Music Genre Identification
AU - Ahmed, Moataz
AU - Fadel, Sherif
AU - Helal, Manal E.
AU - Wahdan, Abdel Moneim
N1 - Published by: Semarak Ilmu Publishing. This is an open-access article distributed under the terms of the Creative Commons Attribution-Non Commercial 4.0 International License (CC BY-NC), https://creativecommons.org/licenses/by-nc/4.0/
PY - 2024/5/22
Y1 - 2024/5/22
N2 - Music Information Retrieval (MIR) is one data science application crucial for different tasks such as recommendation systems, genre identification, fingerprinting, and novelty assessment. Different Machine Learning techniques are utilised to analyse digital music records, such as clustering, classification, similarity scoring, and identifying various properties for the different tasks. Music is represented digitally using diverse transformations and is clustered and classified successfully for Western Music. However, Eastern Music poses a challenge, and some techniques have achieved success in clustering and classifying Turkish and Persian Music. This research presents an evaluation of machine learning algorithms' performance on pre-labelled Arabic Music with their Arabic genre (Maqam). The study introduced new data representations of the Arabic music dataset and identified the most suitable machine-learning methods and future enhancements.
AB - Music Information Retrieval (MIR) is one data science application crucial for different tasks such as recommendation systems, genre identification, fingerprinting, and novelty assessment. Different Machine Learning techniques are utilised to analyse digital music records, such as clustering, classification, similarity scoring, and identifying various properties for the different tasks. Music is represented digitally using diverse transformations and is clustered and classified successfully for Western Music. However, Eastern Music poses a challenge, and some techniques have achieved success in clustering and classifying Turkish and Persian Music. This research presents an evaluation of machine learning algorithms' performance on pre-labelled Arabic Music with their Arabic genre (Maqam). The study introduced new data representations of the Arabic music dataset and identified the most suitable machine-learning methods and future enhancements.
KW - Music Information Retrieval (MIR)
KW - Genre/Maqam Classification
KW - Machine Learning
U2 - 10.37934/araset.46.1.187200
DO - 10.37934/araset.46.1.187200
M3 - Review article
SN - 2462-1943
VL - 46
SP - 187
EP - 200
JO - Journal of Advanced Research in Applied Sciences and Engineering Technology
JF - Journal of Advanced Research in Applied Sciences and Engineering Technology
IS - 1
ER -