DocumentCode :
2445760
Title :
Speech Recognition using Artificial Neural Networks
Author :
Maaly, Iman Abuel ; El-Obaid, Manal
Author_Institution :
Fac. of Eng., Khartoum Univ.
Volume :
1
fYear :
0
fDate :
0-0 0
Firstpage :
1246
Lastpage :
1247
Abstract :
As most of the researches on speech recognition (SR) are based on hidden Markov models (HMM), the main theme of this paper is the recognition of Arabic sounds using artificial neural networks. Despite the fact that Arabic is a language that is spoken by millions of people, and it is the sixth (K. Kirchhoff and J. Bilmes, 2002) spoken language in the world, we have faced a scarcity of researches in Arabic language recognition during the preparation of this paper. Speech recognition systems will become more used as they started to replace some of the functions normally accomplished with a keyboard, these and many other reasons encouraged us to continue in this field
Keywords :
natural languages; neural nets; speech recognition; Arabic language; Arabic sounds recognition; artificial neural network; speech recognition; Artificial neural networks; Cepstral analysis; Databases; Finite impulse response filter; Hidden Markov models; Linear predictive coding; Natural languages; Signal processing algorithms; Speech analysis; Speech recognition; Arabic Phonemes; Neural Networks; Speech Recognition;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Information and Communication Technologies, 2006. ICTTA '06. 2nd
Conference_Location :
Damascus
Print_ISBN :
0-7803-9521-2
Type :
conf
DOI :
10.1109/ICTTA.2006.1684556
Filename :
1684556
Link To Document :
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