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2021 | OriginalPaper | Chapter

Nasheed Song Classification by Fuzzy Soft-Set Approach

Authors : Rabiei Mamat, Ahmad Shukri Mohd Noor, Mustafa Mat Deris

Published in: Computational Science and Technology

Publisher: Springer Singapore

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Abstract

Classification of genres is among the important tasks of musical knowledge discovery. It may affect the accuracy of finding results or reducing the processing time when looking for a certain musical genre in an internet context. While the genre classification scheme looks very promising for western genres, the genre of non-western still has no space in genre retrievals, especially in identifying nasheed song. Therefore, a research has been carried out to select the best features to describe nasheed genre and creates a classifier using the selected features to classify nasheed. The features selection technique and the classifier were built based on the theory of fuzzy-soft set that have enough parameters to handle uncertainties in data. The result show that the built classifier using the selected features accurately can identify the nasheed genre up to 90%.

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Metadata
Title
Nasheed Song Classification by Fuzzy Soft-Set Approach
Authors
Rabiei Mamat
Ahmad Shukri Mohd Noor
Mustafa Mat Deris
Copyright Year
2021
Publisher
Springer Singapore
DOI
https://doi.org/10.1007/978-981-33-4069-5_18

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