Konuşmacının Yaş ve Cinsiyetine Göre Sınıflandırılmasında DVM Çekirdeğinin Etkisi

Year 2020, , 970 - 982, 30.09.2020

Ergün Yücesoy

https://doi.org/10.31202/ecjse.707179

Cited By: 2

Abstract

Bu çalışmada kısa süreli telefon konuşmalarından konuşmacının yaş ve cinsiyet grubunun otomatik olarak belirlemesi konusu ele alınmıştır. Çalışmada Mel Frekansı Kepstrum katsayıları (MFKK) ve bu katsayılardan türetilen delta parametreleri öznitelik olarak kullanılırken yaş ve cinsiyet sınıflarının modellenmesinde Genel Arkaplan Modelinden (GAM) uyarlanarak oluşturulan Gauss Karışım Modelleri (GKM) kullanılmıştır. Her konuşma için oluşturulan GKM modelleri süpervektörlere dönüştürülmüş ve bir Destek Vektör Makinesine (DVM) uygulanarak konuşmacının yaş ve cinsiyet grubuna göre sınıflandırılmıştır. Çalışmada doğrusal, polinomiyal, radya tabanlı (RBF) ve GKM-KL çekirdeği olmak üzer dört farklı DVM çekirdeği kullanılırken GKM bileşen sayısı da 32 ile 512 arasında değiştirilmiştir. aGender veri tabanı ile yapılan testlerde en iyi sınıflandırma oranı 256 bileşenli GKM’lerin GKM-KL çekirdeği ile sınıflandırılması sonucunda % 60.95 olarak elde edilmiştir.

Keywords

Yaş ve cinsiyet tanıma, konuşma işleme, gauss karışım modeli, destek vektör makineleri

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