Acoustic training system for speaker independent continuous arabic speech recognition system

被引：4

作者：

Nofal, M ^{[1
]}

Abdel-Raheem, E ^{[1
]}

El Henawy, H ^{[1
]}

Kader, NA ^{[1
]}

机构：

[1] Ain Shams Univ, Cairo, Egypt

来源：

Proceedings of the Fourth IEEE International Symposium on Signal Processing and Information Technology | 2004年

关键词：

speech processing; language processing;

D O I：

10.1109/ISSPIT.2004.1433721

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

The paper presents an acoustic training system for building acoustic models for a medium vocabulary speaker independent continuous speech recognition system. A speech database is constructed to train the acoustic models. The acoustic models are constructed, and trained. A test set database is constructed to test the accuracy of the acoustic models. Also 4 language models of two main types: bigram and context free grammar, were built and used in tests. Our results show 5.26 % and 2.72 % word error rates for 1340 and 306 words bigram based language models, respectively. Our results show also 0.19 % and 0.99% word error rates for 1340 and 306 words context free grammar based language models, respectively.

引用

页码：200 / 203

页数：4