Quantitative assessment of sound characteristics using the affinity (A), mean affinity (MA), brightness (S), mean contrast (MC), harmonicity (H) and monotony (M) of Gamelan timbre

This study investigates the sound characteristics of Peking Gamelan. The characteristics of Peking Gamelan sound are defined by focusing on acoustics related to the description, composition, and distribution of harmonic and secondary frequencies (high-pitched tones) in a sound. These descriptors are...

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Bibliographic Details
Main Authors: Hamdan, Sinin, Sinin, Aaliyawani Ezzerin, Mohamad Said, Khairul Anwar, Abdullah, Johari
Format: Article
Language:English
Published: Taylor's University Sdn Bhd 2024
Online Access:http://psasir.upm.edu.my/id/eprint/111684/1/2024%20Published%20Peking.pdf
http://psasir.upm.edu.my/id/eprint/111684/
https://jestec.taylors.edu.my/Vol%2019%20Issue%202%20April%202024/19_2_24.pdf
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Institution: Universiti Putra Malaysia
Language: English
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Summary:This study investigates the sound characteristics of Peking Gamelan. The characteristics of Peking Gamelan sound are defined by focusing on acoustics related to the description, composition, and distribution of harmonic and secondary frequencies (high-pitched tones) in a sound. These descriptors are calculated from the Fast Fourier Transform (FFT) spectra using the Python Programming Language. Frequency spectrum characteristics are obtained for each sound from the Peking Gamelan using PicoScope oscilloscopes to investigate the fundamental and overtone frequencies. With this FFT spectrum, we can determine the amplitude a_i for each frequency f_i. The FFT spectrum is essentially a discrete collection of N frequencies (f_i) and N amplitudes (a_i). This paper suggests sound characteristic descriptors that allow for the extraction of sound features from FFT. Sound characteristics are related to the fundamental frequency f_0 and secondary frequency f_i (which exist in FFT). The centroid f_bar indicates the presence of frequencies other than f_0 with amplitude distribution in such a way that f_bar has a magnitude greater than f_0. f_bar does not represent the harmonic nature of sound because it is not correlated with the natural scale series of any musical instrument. The acoustic descriptors used in this work are Affinity (A), Mean Affinity (MA), Brightness (S) or Sharpness, Mean Contrast (MC), Harmonicity (H), and Monotony (M). Peking 1 has the highest affinity (minimum A value). Peking 5 has the brightest sound (maximum S value) and the most harmonic sound (minimum H value). Peking 6 exhibits the greatest increase in amplitude with the largest increase in the M value. Peking 1 shows the greatest decrease in amplitude with the largest decrease in the M value. The MA value of Peking 5 indicates dense secondary sound close to f_bar and has the maximum MC value because its secondary frequencies are very small. The coefficients used can discriminate the differences and similarities in sound characteristics. Mean Affinity (MA) or Mean Contrast (MC) allows musical instruments to be uniquely identified. The coefficients MA, MC, H, and M are sufficient to describe the distribution of harmonics in the FFT.