A robust wavelet-based text-independent speaker identification

被引：2
|
作者：
Phung Trung Nghia
Pham Viet Binh
Nguyen Huu Thai
Nguyen Thanh Ha
Kumsawat, Prayoth
机构：
来源：
ICCIMA 2007: INTERNATIONAL CONFERENCE ON COMPUTATIONAL INTELLIGENCE AND MULTIMEDIA APPLICATIONS, VOL II, PROCEEDINGS | 2007年
关键词：
D O I：
10.1109/ICCIMA.2007.149
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
This study proposes novel robust text-independent speaker identification based on the Discrete Wavelet Transform (DWT), the Mel-Frequency Discrete Wavelet Coefficients (MFD WC), the wavelet-based sub-band weighting and the Likelihood Combination Gaussian Mixture Model (LCGMM). This method is used in the text-independent speaker identification in compare to the widely used MFCC features recognizer, full-band recognizer and equal sub-band weighting recognizer. Our experimental results show that our proposal achieves higher recognition rate than the others for our Vietnamese speech corpus with clean and white noisy speech.
引用
收藏
页码：219 / 223
页数：5
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