Automatic Speaker Recognition System Using Fuzzy C-Means Artificial Neural Networks

Speaker recognition is a process of recognizing someone by their voice. The goal of speaker recognition is to extract, characterize and recognize the information about speaker identity. In this paper, we discussed both Fuzzy C-Means (FCM) and Artificial Neural Network (ANN) approach to speaker recog...

وصف كامل

محفوظ في:
التفاصيل البيبلوغرافية
المؤلفون الرئيسيون: M. Z., Ibrahim, Marzuki, Khalid, Rubiyah, Yusof
التنسيق: مقال
اللغة:English
English
منشور في: Universiti Malaysia Pahang 2008
الموضوعات:
الوصول للمادة أونلاين:http://umpir.ump.edu.my/id/eprint/8755/1/fkee-2008-zamri-%20Automatic%20Speaker%20Recognition%20System.pdf
http://umpir.ump.edu.my/id/eprint/8755/7/fkee-2008-zamri-%20Automatic%20Speaker%20Recognition%20System1.pdf
http://umpir.ump.edu.my/id/eprint/8755/
http://www.ump.edu.my/
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المؤسسة: Universiti Malaysia Pahang Al-Sultan Abdullah
اللغة: English
English
الوصف
الملخص:Speaker recognition is a process of recognizing someone by their voice. The goal of speaker recognition is to extract, characterize and recognize the information about speaker identity. In this paper, we discussed both Fuzzy C-Means (FCM) and Artificial Neural Network (ANN) approach to speaker recognition system. The proposed system comprises of three main modules, a feature extraction module to extract necessary features from speech waves, speaker modeling module to generate the speaker model and FCM and ANN module to classify the speakers whether to accept or reject. The proposed intelligent learning system has been applied to a case study of text-dependent speaker recognition system and the performance is evaluated by applying two types of feature extraction techniques: Mel Frequency Cepstral Coefficients (MFCC) and Linear Predictive Ceps~ral Coefficients (LPCC). Experiment showed that the new proposed systems provide significantly higher performance compare to conventional method.