Speech Recognition using Support Vector Machines

被引：0

作者：

Aida-zade, Kamil ^{[1
]}

Xocayev, Anar ^{[2
]}

Rustamov, Samir ^{[3
]}

机构：

[1] Azerbaijan Natl Acad Sci, Inst Control Syst, Baku, Azerbaijan

[2] Qafqaz Univ, Comp Engn, Baku, Azerbaijan

[3] ADA Univ, Azerbaijan Natl Acad Sci, Inst Control Syst, Baku, Azerbaijan

来源：

2016 IEEE 10TH INTERNATIONAL CONFERENCE ON APPLICATION OF INFORMATION AND COMMUNICATION TECHNOLOGIES (AICT) | 2016年

关键词：

Speech Recognition; Feature Extraction; Support Vector Machines; Linear Predictive Coding; Mel Frequency Cepstral Coefficients;

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

In this article we applied Support Vector Machines to acoustic model of Speech Recognition System based on MFCC and LPC features for Azerbaijani DataSet. This DataSet has been used for speech recognition by Multilayer Artificial Neural Network and achieved some results. The main goal of this work is applying SVM techniques to the Azerbaijan Speech Recognition System. The variety of results of SVM with different Kernel functions is analyzed in the training process. It is shown that SVM with radial basis and polynomial kernels give better recognition results that Multilayer Artificial Neural Network.

引用

页码：108 / 111

页数：4

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