TWO-STAGE DECISION MAKING ALGORITHM FOR SPEAKER VERIFICATION WITH TRAINING SET OPTIMIZATION

Yıl 2019, , 48 - 58, 28.01.2019

Efe Tankut Yaparoğlu Yavuz Şenol

https://doi.org/10.28948/ngumuh.516805

Öz

   In this
paper, a two-stage decision making algorithm is proposed for the task of
speaker verification. This two-stage algorithm aims to eliminate the
first-stage qualifying impostors by the help of impostor-resistant structure in
the second stage. First, a baseline system is formed using mel-frequency
cepstral coefficients (MFCC) as features and, a radial basis function (RBF)
neural network for speaker modelling. Then, the investigations have been
realized for optimizing the training set by means of two issues: (1) the ratio
of impostor features to genuine speaker features, (2) the ratio of same gender
features to opposite gender features (in respect of the genuine speaker) within
the impostor speakers’ set. Last, the two-stage decision making algorithm is presented,
and the performance enhancement provided by the two-stage system is given with
the test results.

Anahtar Kelimeler

Speaker verification, Training set optimization, RBF neural network, MFCC, Cohort

KONUŞMACI DOĞRULAMA İÇİN EĞİTİM SETİ OPTİMİZASYONLU İKİ AŞAMALI KARAR VERME ALGORİTMASI

Öz

   Bu çalışmada, konuşmacı doğrulama görevi
için iki aşamalı bir karar verme algoritması önerilmiştir. Bu iki aşamalı
algoritma, ikinci aşamada sahtekarlara dayanıklı yapı sayesinde ilk aşamayı
geçen sahtekârları ortadan kaldırmayı amaçlıyor. Birinci aşamada, öznitelik
olarak mel-frekanslı sepstral katsayılar (MFCC) kullanılarak temel bir sistem
oluşturulmuş ve bir radyal taban fonksiyonu (RBF) sinir ağı kullanılarak
konuşmacı modellemesi gerçekleştirilmiştir. Ardından, eğitim setini iki kısımda
optimize etmek için araştırmalar gerçekleştirildi: (1) taklitçi konuşmacı
özniteliklerinin gerçek konuşmacı özniteliklerine oranı, (2) taklitçi konuşmacı
kümesi içinde aynı cinsiyet özniteliklerinin zıt cinsiyet özniteliklerine oranı
(gerçek konuşmacıya bağlı olarak). Son olarak, iki aşamalı karar verme
algoritması sunulmuş ve iki aşamalı sistem tarafından sağlanan performans
artışı test sonuçlarıyla birlikte verilmiştir.

Anahtar Kelimeler

Konuşmacı doğrulama, Eğitim kümesi optimizasyonu, RBF yapay sinir ağları, MFCC, Cohort

Kaynakça

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