GMM Optimization Using Neural Networks for Persian Language Detection

摘要：

In this paper Persian language verification system is proposed and evaluated. This technique is constructed by using Gaussian mixture models as a basic system for tokenizing and a Neural Network as the backend processor. Performances result are presented for a used system of GMM Tokenizer in combining with Neural Network and finally the results of GMM-NN system compared with GMM-Tokenizer system. It will be shown that using the Neural Network as the backend processor will improve the results significantly.

作者: A.Shadmand R.Shaghaghi kandovan F.Razzazi Y.Etemad

作者单位: EE Department, Islamic Azad University, Najaf Abad Branch, Najaf Abad, Esfahan, Iran EE Department, Islamic Azad University, ShahreRay Branch, Tehran, Iran EE Department, Islamic Azad University, Science & Research Branch, Tehran, Iran

会议类型: 国际会议

会议名称: The Second International Joint Conference on Computational Science and Optimization(CSO 2009)(2009 国际计算科学与优化会议)

会议地点: 三亚

会议语种:英文

页码: 922-924

在线出版日期: 2009-04-24（万方平台首次上网日期，不代表论文的发表时间）