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...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English English |
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Universiti Malaysia Pahang
2008
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| Subjects: | |
| Online Access: | http://umpir.ump.edu.my/id/eprint/8755/ 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 |
| _version_ | 1848818323196739584 |
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| author | M. Z., Ibrahim Marzuki, Khalid Rubiyah, Yusof |
| author_facet | M. Z., Ibrahim Marzuki, Khalid Rubiyah, Yusof |
| author_sort | M. Z., Ibrahim |
| building | UMP Institutional Repository |
| collection | Online Access |
| description | 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. |
| first_indexed | 2025-11-15T01:35:50Z |
| format | Article |
| id | ump-8755 |
| institution | Universiti Malaysia Pahang |
| institution_category | Local University |
| language | English English |
| last_indexed | 2025-11-15T01:35:50Z |
| publishDate | 2008 |
| publisher | Universiti Malaysia Pahang |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | ump-87552016-09-05T03:04:53Z http://umpir.ump.edu.my/id/eprint/8755/ Automatic Speaker Recognition System Using Fuzzy C-Means Artificial Neural Networks M. Z., Ibrahim Marzuki, Khalid Rubiyah, Yusof TK Electrical engineering. Electronics Nuclear engineering 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. Universiti Malaysia Pahang 2008 Article PeerReviewed application/pdf en http://umpir.ump.edu.my/id/eprint/8755/1/fkee-2008-zamri-%20Automatic%20Speaker%20Recognition%20System.pdf application/pdf en http://umpir.ump.edu.my/id/eprint/8755/7/fkee-2008-zamri-%20Automatic%20Speaker%20Recognition%20System1.pdf M. Z., Ibrahim and Marzuki, Khalid and Rubiyah, Yusof (2008) Automatic Speaker Recognition System Using Fuzzy C-Means Artificial Neural Networks. Jurnal UMP Kejuruteraan & Teknologi Komputer, 1 (1). pp. 93-108. ISSN 1985-5176. (Published) http://www.ump.edu.my/ |
| spellingShingle | TK Electrical engineering. Electronics Nuclear engineering M. Z., Ibrahim Marzuki, Khalid Rubiyah, Yusof Automatic Speaker Recognition System Using Fuzzy C-Means Artificial Neural Networks |
| title | Automatic Speaker Recognition System Using Fuzzy C-Means Artificial Neural Networks |
| title_full | Automatic Speaker Recognition System Using Fuzzy C-Means Artificial Neural Networks |
| title_fullStr | Automatic Speaker Recognition System Using Fuzzy C-Means Artificial Neural Networks |
| title_full_unstemmed | Automatic Speaker Recognition System Using Fuzzy C-Means Artificial Neural Networks |
| title_short | Automatic Speaker Recognition System Using Fuzzy C-Means Artificial Neural Networks |
| title_sort | automatic speaker recognition system using fuzzy c-means artificial neural networks |
| topic | TK Electrical engineering. Electronics Nuclear engineering |
| url | http://umpir.ump.edu.my/id/eprint/8755/ http://umpir.ump.edu.my/id/eprint/8755/ 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 |