التفاصيل البيبلوغرافية
العنوان: |
Identification of violin timbre by neural network using acoustic features. |
المؤلفون: |
Masao Yokoyama, Yuya Ishigaki |
المصدر: |
Proceedings of Meetings on Acoustics; 9/11/2022, Vol. 49 Issue 1, p1-8, 8p |
مصطلحات موضوعية: |
VIOLIN strings, ACOUSTICS, MACHINE learning, CEPSTRUM analysis (Mechanics), NEURAL computers, TONE color (Music theory) |
مستخلص: |
The timbre of violins is identified using machine learning, and a computer program is developed for the neural network using Python and Keras libraries. The 21 violins recorded include old Italian violins made by Stradivari and contemporary violins. The training and test data use the spectrum envelope and Melfrequency cepstrum coefficients (MFCC). The accuracy of the identification test in the case of open strings is greater than 90%. Furthermore, experiments that predict similarity in timbre of an unknown violin to that of trained violins are presented. [ABSTRACT FROM AUTHOR] |
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قاعدة البيانات: |
Complementary Index |