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Research on Hierarchical Speaker Recognition System Based on LS-SVM

Author: ZhangJing
Tutor: ZhaoZhenDong
School: North China Electric Power University (Hebei)
Course: Communication and Information System
Keywords: Speaker Recognition Least squares support vector machine Principal Component Analysis Robustness
CLC: TN912.34
Type: Master's thesis
Year: 2010
Downloads: 85
Quote: 0
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Abstract


Speaker recognition is based on the parameters of the speech waveform reflect speaker physiological and behavioral characteristics , automatically identify the speaker . Speaker recognition technology is widely used as a biometric authentication technology , Internet communications , banking and other fields . This paper describes the voice signal preprocessing , feature extraction and anti-noise and speaker recognition method based on principal component analysis (PCA) and least squares support vector machine (LS-SVM) . PT LS-SVM - based speaker recognition model is constructed , a large number of experiments and the identification model performance for large population speaker recognition system . The experimental results show that this method can achieve good recognition performance in noisy environments , and the system has good robustness .

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CLC: > Industrial Technology > Radio electronics, telecommunications technology > Communicate > Electro-acoustic technology and speech signal processing > Speech Signal Processing > Speech Recognition and equipment
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