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

Abstract

   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.

Keywords

• 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

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