The musical descriptor using Fast Fourier Transform (FFT): examples in P Ramlee songs
Abstract The musical descriptor can be characterize using quantitative evaluation of audio sounds. This paper evaluates the musical descriptors for P Ramlee instrumental songs utilizing the Fast Fourier Transform (FFT) from the audio sounds signal. In this study, Python programming language is us...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
University of Brunei Darussalam
2024
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| Subjects: | |
| Online Access: | http://psasir.upm.edu.my/id/eprint/114519/ http://psasir.upm.edu.my/id/eprint/114519/1/114519.pdf |
| _version_ | 1848866517681176576 |
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| author | Musib, Ahmad Faudzi Hamdan, Sinin Kuryati, Kipli Sinin, Aaliyawani Ezzerin Johari Abdullah, Johari Abdullah |
| author_facet | Musib, Ahmad Faudzi Hamdan, Sinin Kuryati, Kipli Sinin, Aaliyawani Ezzerin Johari Abdullah, Johari Abdullah |
| author_sort | Musib, Ahmad Faudzi |
| building | UPM Institutional Repository |
| collection | Online Access |
| description | Abstract
The musical descriptor can be characterize using quantitative evaluation of audio sounds. This paper evaluates the
musical descriptors for P Ramlee instrumental songs utilizing the Fast Fourier Transform (FFT) from the audio sounds
signal. In this study, Python programming language is used to develop a series of custom scripts to calculate the musical
descriptors. The approach involved constructing musical descriptors from instrumental music through analysis and
digital processing of the spectra. The signal data were first transformed using the FFT to extract frequencies and intensities,
which are crucial for identifying the spectral signature of musical sounds. The FFT is particularly valuable as it
uniquely represents the spectral content of any musical sound by transforming the time-domain signal into its frequency-
domain components. The Affinity coefficient, A, increased from 1.43 (Jangan Tinggal Daku) to 6.67 (Dendang
Perantau), 8.96 (Di Pinggiran) and 13.81 (Getaran Jiwa). The Sharpness coefficient, S for Di Pinggiran is 0.039, Getaran
Jiwa is 0.040, Dendang Perantau is 0.056 and Jangan Tinggal Daku is 0.065. The Harmonicity coefficient H for Di
Pinggiran showed the highest H i.e. 17.0 followed by Dendang Perantau i.e. 8.2, Jangan Tinggal Daku i.e. 7.5 and
Getaran Jiwa i.e. only 5.0. Monotony coefficient M of Dendang Perantau showed the lowest M i.e. ¡0.0096 followed by
Di Pinggiran i.e. ¡0.0013, Jangan Tinggal Daku i.e. 0.0198 and Getaran Jiwa i.e. 0.0638. The Mean Affinity (MA) increase
from 0.1689 (Getaran Jiwa) to 0.5322 (Dendang Perantau), 0.8673 (Di Pinggiran) and 1.3877 (Jangan Tinggal Daku). The
Mean Contrast (MC) increase from 0.1568 (Di Pinggiran) to 0.3160 (Dendang Perantau), 0.4430 (Jangan Tinggal Daku)
and 0.4755 (Getaran Jiwa).
Keywords: Affinity, Sharpness, Harmonicity, Monotony, Mean Affinity and Mean Contrast |
| first_indexed | 2025-11-15T14:21:52Z |
| format | Article |
| id | upm-114519 |
| institution | Universiti Putra Malaysia |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-15T14:21:52Z |
| publishDate | 2024 |
| publisher | University of Brunei Darussalam |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | upm-1145192025-01-22T03:49:17Z http://psasir.upm.edu.my/id/eprint/114519/ The musical descriptor using Fast Fourier Transform (FFT): examples in P Ramlee songs Musib, Ahmad Faudzi Hamdan, Sinin Kuryati, Kipli Sinin, Aaliyawani Ezzerin Johari Abdullah, Johari Abdullah Abstract The musical descriptor can be characterize using quantitative evaluation of audio sounds. This paper evaluates the musical descriptors for P Ramlee instrumental songs utilizing the Fast Fourier Transform (FFT) from the audio sounds signal. In this study, Python programming language is used to develop a series of custom scripts to calculate the musical descriptors. The approach involved constructing musical descriptors from instrumental music through analysis and digital processing of the spectra. The signal data were first transformed using the FFT to extract frequencies and intensities, which are crucial for identifying the spectral signature of musical sounds. The FFT is particularly valuable as it uniquely represents the spectral content of any musical sound by transforming the time-domain signal into its frequency- domain components. The Affinity coefficient, A, increased from 1.43 (Jangan Tinggal Daku) to 6.67 (Dendang Perantau), 8.96 (Di Pinggiran) and 13.81 (Getaran Jiwa). The Sharpness coefficient, S for Di Pinggiran is 0.039, Getaran Jiwa is 0.040, Dendang Perantau is 0.056 and Jangan Tinggal Daku is 0.065. The Harmonicity coefficient H for Di Pinggiran showed the highest H i.e. 17.0 followed by Dendang Perantau i.e. 8.2, Jangan Tinggal Daku i.e. 7.5 and Getaran Jiwa i.e. only 5.0. Monotony coefficient M of Dendang Perantau showed the lowest M i.e. ¡0.0096 followed by Di Pinggiran i.e. ¡0.0013, Jangan Tinggal Daku i.e. 0.0198 and Getaran Jiwa i.e. 0.0638. The Mean Affinity (MA) increase from 0.1689 (Getaran Jiwa) to 0.5322 (Dendang Perantau), 0.8673 (Di Pinggiran) and 1.3877 (Jangan Tinggal Daku). The Mean Contrast (MC) increase from 0.1568 (Di Pinggiran) to 0.3160 (Dendang Perantau), 0.4430 (Jangan Tinggal Daku) and 0.4755 (Getaran Jiwa). Keywords: Affinity, Sharpness, Harmonicity, Monotony, Mean Affinity and Mean Contrast University of Brunei Darussalam 2024-11-25 Article PeerReviewed text en http://psasir.upm.edu.my/id/eprint/114519/1/114519.pdf Musib, Ahmad Faudzi and Hamdan, Sinin and Kuryati, Kipli and Sinin, Aaliyawani Ezzerin and Johari Abdullah, Johari Abdullah (2024) The musical descriptor using Fast Fourier Transform (FFT): examples in P Ramlee songs. ASEAN Journal on Science and Technology for Development, 41 (3). pp. 279-291. ISSN 0217-5460; eISSN: 2224-9028 https://ajstd.ubd.edu.bn/journal/vol41/iss3/7/ Music 10.61931/2224-9028.1601 |
| spellingShingle | Music Musib, Ahmad Faudzi Hamdan, Sinin Kuryati, Kipli Sinin, Aaliyawani Ezzerin Johari Abdullah, Johari Abdullah The musical descriptor using Fast Fourier Transform (FFT): examples in P Ramlee songs |
| title | The musical descriptor using Fast Fourier Transform (FFT): examples in P Ramlee songs |
| title_full | The musical descriptor using Fast Fourier Transform (FFT): examples in P Ramlee songs |
| title_fullStr | The musical descriptor using Fast Fourier Transform (FFT): examples in P Ramlee songs |
| title_full_unstemmed | The musical descriptor using Fast Fourier Transform (FFT): examples in P Ramlee songs |
| title_short | The musical descriptor using Fast Fourier Transform (FFT): examples in P Ramlee songs |
| title_sort | musical descriptor using fast fourier transform (fft): examples in p ramlee songs |
| topic | Music |
| url | http://psasir.upm.edu.my/id/eprint/114519/ http://psasir.upm.edu.my/id/eprint/114519/ http://psasir.upm.edu.my/id/eprint/114519/ http://psasir.upm.edu.my/id/eprint/114519/1/114519.pdf |