A study of speech recognition system based on the Hidden Markov Model with Gaussian-Mixture

被引：0
|
作者：
Ben Hazem, Zied [1 ]
Zouhir, Youssef [1 ]
Ouni, Kais [1 ]
机构：
[1] Univ Carthage, Higher Sch Technol & Comp Sci ESTI, Res Unit Signals & Mechatron Syst, SMS, Carthage, Tunisia
来源：
2014 INTERNATIONAL CONFERENCE ON ELECTRICAL SCIENCES AND TECHNOLOGIES IN MAGHREB (CISTEM) | 2014年
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D O I：
暂无
中图分类号：
T [工业技术];
学科分类号：
08 ;
摘要：
In this paper, we present a study of isolated word speech recognition system. The adopted system is based on the Hidden Markov Model with Gaussian Mixture (HMM-GM). We studied the recognition rate by varying the states number (3, 4, 5, 6 and 7 states) and the number of Gaussians per state (2, 4, 8, 12, 14 and 16 Gaussians) of Hidden Markov Model. We evaluated these recognition rates using two parameterization techniques Mel Frequency Cepstral Coefficients (MFCC) and Perceptual Linear Prediction (PLP). We have introduced the dynamic coefficients and the energy of the signal in order to achieve an improvement in the recognition rate.
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页数：5
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