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SÜREKLİ SAKLI MARKOV MODELLERİ İLE METİNDEN BAĞIMSIZ KONUŞMACI TANIMA PARAMETRELERİNİN İNCELENMESİ

On the Parameters of Text-Independent Speaker Identification Using Continuous HMMs

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Abstract (2. Language): 
In this paper, the parameters of text-independent speaker identification system (size of feature vector, number of states and mixtures) using Hidden Markov Models (HMMs) of both ergodic and left-to-right type have been analyzed in relation to identification rate, and their optimum values have been determined.
Abstract (Original Language): 
Bu çalışmada, ergodik ve soldan-sağa olmak üzere iki farklı saklı Markov modelleri kullanan metinden bağımsız konuşmacı tanıma sistemine ilişkin parametreler (özellik vektörü boyutu, model durum ve karışım sayıları) tanıma başarımına etkisi yönünden karşılaştırmalı olarak incelenmiş ve bunların optimum değerleri belirlenmiştir.
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