Analysing sound characteristics of cello and violin using fast fourier transform
The unique sound characteristics of music are based on multiple harmonic frequencies that exist within the sound waves. Through Fast Fourier Transform (FFT) software, the wave can be broken down into frequency and amplitude components. Spectrum analysis can be used quantitatively to describe these s...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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University of Brunei Darussalam
2024
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| Online Access: | http://psasir.upm.edu.my/id/eprint/116713/ http://psasir.upm.edu.my/id/eprint/116713/1/116713.pdf |
| _version_ | 1848867073314258944 |
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| author | Hamdan, Sinin Mohamad Said, Khairul A. Musib, Ahmad F. Sawawi, Marini Sinin, Aaliyawani E. |
| author_facet | Hamdan, Sinin Mohamad Said, Khairul A. Musib, Ahmad F. Sawawi, Marini Sinin, Aaliyawani E. |
| author_sort | Hamdan, Sinin |
| building | UPM Institutional Repository |
| collection | Online Access |
| description | The unique sound characteristics of music are based on multiple harmonic frequencies that exist within the sound waves. Through Fast Fourier Transform (FFT) software, the wave can be broken down into frequency and amplitude components. Spectrum analysis can be used quantitatively to describe these sound characteristics. In this paper, the frequency range present in the spectrum and the average intensity of the first 10 high notes in the sound are used to classify the sound characteristics of the cello and violin. This is done by generating a frequency (x-axis) and amplitude (y-axis) graph for the sounds of the cello and violin. The frequency and amplitudes are used to calculate 7 descriptors for sound characteristics, namely the centroid (f) Affinity (A), Brightness or Sharpness (S), Harmonicity (H), Monotony (M), Mean Affinity (MA), and Mean Contrast (MC). The results of the research reveal that quantitative frequency data analysis can generate and map sound characteristics. Quantitative analysis allows the quality of sound characteristics to be transformed into information understood by the computer. Eurostring cello string C2 is the most affinity (having a minimum A value, approaching 1, indicating that fo and f are close). Eurostring violin string D4 have the brightest sound (maximum S value). Stradivarius copy violin strings D4 is the most harmonic (having a minimum H value, approaching 0). Eurostring cello string C2 shows harmonics present in most successive reductions (negative M) after fo. The MA value of Spicato cello C2 indicates dense secondary sound and is close to f . The maximum MC value of Eurostring violin string D4 indicates normalized amplitude for its high-secondary frequency. |
| first_indexed | 2025-11-15T14:30:42Z |
| format | Article |
| id | upm-116713 |
| institution | Universiti Putra Malaysia |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-15T14:30:42Z |
| publishDate | 2024 |
| publisher | University of Brunei Darussalam |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | upm-1167132025-04-15T03:22:55Z http://psasir.upm.edu.my/id/eprint/116713/ Analysing sound characteristics of cello and violin using fast fourier transform Hamdan, Sinin Mohamad Said, Khairul A. Musib, Ahmad F. Sawawi, Marini Sinin, Aaliyawani E. The unique sound characteristics of music are based on multiple harmonic frequencies that exist within the sound waves. Through Fast Fourier Transform (FFT) software, the wave can be broken down into frequency and amplitude components. Spectrum analysis can be used quantitatively to describe these sound characteristics. In this paper, the frequency range present in the spectrum and the average intensity of the first 10 high notes in the sound are used to classify the sound characteristics of the cello and violin. This is done by generating a frequency (x-axis) and amplitude (y-axis) graph for the sounds of the cello and violin. The frequency and amplitudes are used to calculate 7 descriptors for sound characteristics, namely the centroid (f) Affinity (A), Brightness or Sharpness (S), Harmonicity (H), Monotony (M), Mean Affinity (MA), and Mean Contrast (MC). The results of the research reveal that quantitative frequency data analysis can generate and map sound characteristics. Quantitative analysis allows the quality of sound characteristics to be transformed into information understood by the computer. Eurostring cello string C2 is the most affinity (having a minimum A value, approaching 1, indicating that fo and f are close). Eurostring violin string D4 have the brightest sound (maximum S value). Stradivarius copy violin strings D4 is the most harmonic (having a minimum H value, approaching 0). Eurostring cello string C2 shows harmonics present in most successive reductions (negative M) after fo. The MA value of Spicato cello C2 indicates dense secondary sound and is close to f . The maximum MC value of Eurostring violin string D4 indicates normalized amplitude for its high-secondary frequency. University of Brunei Darussalam 2024 Article PeerReviewed text en cc_by_sa_4 http://psasir.upm.edu.my/id/eprint/116713/1/116713.pdf Hamdan, Sinin and Mohamad Said, Khairul A. and Musib, Ahmad F. and Sawawi, Marini and Sinin, Aaliyawani E. (2024) Analysing sound characteristics of cello and violin using fast fourier transform. ASEAN Journal on Science and Technology for Development, 41 (3). pp. 292-308. ISSN 0217-5460; eISSN: 2224-9028 https://ajstd.ubd.edu.bn/journal/vol41/iss3/8/ 10.61931/2224-9028.1602 |
| spellingShingle | Hamdan, Sinin Mohamad Said, Khairul A. Musib, Ahmad F. Sawawi, Marini Sinin, Aaliyawani E. Analysing sound characteristics of cello and violin using fast fourier transform |
| title | Analysing sound characteristics of cello and violin using fast fourier transform |
| title_full | Analysing sound characteristics of cello and violin using fast fourier transform |
| title_fullStr | Analysing sound characteristics of cello and violin using fast fourier transform |
| title_full_unstemmed | Analysing sound characteristics of cello and violin using fast fourier transform |
| title_short | Analysing sound characteristics of cello and violin using fast fourier transform |
| title_sort | analysing sound characteristics of cello and violin using fast fourier transform |
| url | http://psasir.upm.edu.my/id/eprint/116713/ http://psasir.upm.edu.my/id/eprint/116713/ http://psasir.upm.edu.my/id/eprint/116713/ http://psasir.upm.edu.my/id/eprint/116713/1/116713.pdf |