Design and Implementation of a Microphone Array Based Speaker Recognition System
碩士 === 國立中央大學 === 資訊工程學系在職專班 === 105 === The study is to design an embedded speaker identification system based on microphone array in order to improve the efficiency of single microphone identification systems. The system is composed of four modules including sound signal extraction from microphone...
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ndltd-TW-105NCU053920602017-10-22T04:29:51Z http://ndltd.ncl.edu.tw/handle/75364770280146060498 Design and Implementation of a Microphone Array Based Speaker Recognition System 基於麥克風陣列的語者辨識系統設計與實作 Jen-Nan Yu 游仁男 碩士 國立中央大學 資訊工程學系在職專班 105 The study is to design an embedded speaker identification system based on microphone array in order to improve the efficiency of single microphone identification systems. The system is composed of four modules including sound signal extraction from microphone array, beam forming, speaker features extraction and speaker identification module. Sound signal module is to collect speaker sound information by using loop microphone array composed of Micro Electro Mechanical System (MEMS) microphone; Beam forming is to enhance sound signal and remove background noise via multi-channel sound processing; Linear Predictive Cepstrum Coefficient (LPCC) is applied to represent a speaker sound characteristics module; The classifier of Probabilistic Neural Network (PNN) is applied to identify speaker. Besides, we built a database of experimental speaker sounds with one hundred and twenty same statements recorded by twelve people. This is to validate the speaker identification system. The recognition rate was optimized by PNN smoothing parameters and beam forming parameters during the training. The test results showed that our speaker identification system based on microphone array could reduce about 10% error rate compared to the single one. Ching-Han Chen 陳慶瀚 2017 學位論文 ; thesis 77 zh-TW |
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碩士 === 國立中央大學 === 資訊工程學系在職專班 === 105 === The study is to design an embedded speaker identification system based on microphone array in order to improve the efficiency of single microphone identification systems. The system is composed of four modules including sound signal extraction from microphone array, beam forming, speaker features extraction and speaker identification module. Sound signal module is to collect speaker sound information by using loop microphone array composed of Micro Electro Mechanical System (MEMS) microphone; Beam forming is to enhance sound signal and remove background noise via multi-channel sound processing; Linear Predictive Cepstrum Coefficient (LPCC) is applied to represent a speaker sound characteristics module; The classifier of Probabilistic Neural Network (PNN) is applied to identify speaker. Besides, we built a database of experimental speaker sounds with one hundred and twenty same statements recorded by twelve people. This is to validate the speaker identification system. The recognition rate was optimized by PNN smoothing parameters and beam forming parameters during the training. The test results showed that our speaker identification system based on microphone array could reduce about 10% error rate compared to the single one.
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Ching-Han Chen |
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Ching-Han Chen Jen-Nan Yu 游仁男 |
author |
Jen-Nan Yu 游仁男 |
spellingShingle |
Jen-Nan Yu 游仁男 Design and Implementation of a Microphone Array Based Speaker Recognition System |
author_sort |
Jen-Nan Yu |
title |
Design and Implementation of a Microphone Array Based Speaker Recognition System |
title_short |
Design and Implementation of a Microphone Array Based Speaker Recognition System |
title_full |
Design and Implementation of a Microphone Array Based Speaker Recognition System |
title_fullStr |
Design and Implementation of a Microphone Array Based Speaker Recognition System |
title_full_unstemmed |
Design and Implementation of a Microphone Array Based Speaker Recognition System |
title_sort |
design and implementation of a microphone array based speaker recognition system |
publishDate |
2017 |
url |
http://ndltd.ncl.edu.tw/handle/75364770280146060498 |
work_keys_str_mv |
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