Machine learning based classification of violin and viola instrument sounds for the same notes [Keman ve Viyola Çalgi Seslerinin Ayni Notalar için Makine Ögrenme Tabanli Siniflandirilmasi]
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Dosyalar
Tarih
2018
Yazarlar
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Institute of Electrical and Electronics Engineers Inc.
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
In this paper, a study on the classification of violin and viola instrument sounds in the same notes that are hard for people to distinguish is presented. First, 16 statistical features defined in the time and frequency domain for 512 violin note recordings and 512 viola note recordings are extracted. Classification algorithms including Linear Distinction Analysis (LDA), k-nearest neighbors (k-NN), Support Vector Machines (SVM), and Random Forests (RF) classifiers are used to recognize violin and viola instrument sounds. The classification operation is performed on three different sets of features: only time domain features (12), only frequency domain features (4), and both time domain and frequency domain features (16). Simulation results show that the highest accuracy rate is obtained when using the Random Forests classifier with both time and frequency domain attributes. With Random Forest classifier, while obtaining 64.4% classification accuracy with 10 times cross-validity using only time domain and only frequency domain features, 79.6% classification success is achieved with both time and frequency domain features. © 2018 IEEE.
Açıklama
Aselsan;et al.;Huawei;IEEE Signal Processing Society;IEEE Turkey Section;Netas
26th IEEE Signal Processing and Communications Applications Conference, SIU 2018 -- 2 May 2018 through 5 May 2018 -- -- 137780
26th IEEE Signal Processing and Communications Applications Conference, SIU 2018 -- 2 May 2018 through 5 May 2018 -- -- 137780
Anahtar Kelimeler
Feature extraction, Instrument classification, Machine learning, Music signal processing, Random forests, Viola, Violin
Kaynak
26th IEEE Signal Processing and Communications Applications Conference, SIU 2018
WoS Q Değeri
Scopus Q Değeri
N/A
