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Mel-Frequency-based Feature Analysis of Audio Signals in the Context of Holy Quran Recitation.
- Source :
-
Arabian Journal for Science & Engineering (Springer Science & Business Media B.V. ) . May2024, Vol. 49 Issue 5, p6971-6979. 9p. - Publication Year :
- 2024
-
Abstract
- Different sounds have various effects on human health, and by introducing the ones that are therapeutic, a healing environment can be created. This paper describes the process to train and test a machine learning algorithm to describe and explore the therapeutic nature of Quranic verse. Using a dataset containing four emotional states namely happy, sad, angry, and relaxed, we trained a model and classified different recitations of the Quran into one of these states. This paper proposes the use of Mel-frequency cepstral coefficients (MFCC) to extract features from Quranic audio and classify it with respect to a known dataset. Based on the experiments conducted on Quranic verses, we summarize our results. [ABSTRACT FROM AUTHOR]
- Subjects :
- *EMOTIONAL state
*MACHINE learning
*HEALING
Subjects
Details
- Language :
- English
- ISSN :
- 2193567X
- Volume :
- 49
- Issue :
- 5
- Database :
- Academic Search Index
- Journal :
- Arabian Journal for Science & Engineering (Springer Science & Business Media B.V. )
- Publication Type :
- Academic Journal
- Accession number :
- 176689463
- Full Text :
- https://doi.org/10.1007/s13369-023-08555-5