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CORR
2008
Springer

Probabilistic SVM/GMM Classifier for Speaker-Independent Vowel Recognition in Continues Speech

13 years 3 months ago
Probabilistic SVM/GMM Classifier for Speaker-Independent Vowel Recognition in Continues Speech
In this paper, we discuss the issues in automatic recognition of vowels in Persian language. The present work focuses on new statistical method of recognition of vowels as a basic unit of syllables. First we describe a vowel detection system then briefly discuss how the detected vowels can feed to recognition unit. According to pattern recognition, Support Vector Machines (SVM) as a discriminative classifier and Gaussian mixture model (GMM) as a generative model classifier are two most popular techniques. Current state-ofthe-art systems try to combine them together for achieving more power of classification and improving the performance of the recognition systems. The main idea of the study is to combine probabilistic SVM and traditional GMM pattern classification with some characteristic of speech like band-pass energy to achieve better classification rate. This idea has been analytically formulated and tested on a FarsDat based vowel recognition system. The results show inconceivabl...
Mohammad Nazari, Abolghasem Sayadiyan, Seyyed Maji
Added 10 Dec 2010
Updated 10 Dec 2010
Type Journal
Year 2008
Where CORR
Authors Mohammad Nazari, Abolghasem Sayadiyan, Seyyed Majid Valiollahzadeh
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