Isolated words recognition using neural networks

被引:0
|
作者
Harb, H
机构
来源
ICECS 2000: 7TH IEEE INTERNATIONAL CONFERENCE ON ELECTRONICS, CIRCUITS & SYSTEMS, VOLS I AND II | 2000年
关键词
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Because anyone would like to speak with his machine, we decided to make a speech recognition project. Our objective is to recognize a word to use it as an industrial machine's command, with good accuracy and performance. Till now methods used in speech recognition are analytical or statistical methods. Analytical methods like DTW or Euclidian distance have been used for isolated words recognition, but the performance wasn't good enough (noise makes problems with these methods)Statistical methods, especially Multi layer preceptron with hidden Markov Model (MLP+HMM) are commonly used these days, for both continuous and isolated speech, because of their good performance (better than analytical methods)Our method consists of using just Neural Networks for the recognition of a number of words (commands).
引用
收藏
页码:349 / 351
页数:3
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