DocumentCode :
2957387
Title :
A novel approach to increase the robustness of speaker independent Arabic speech recognition
Author :
Shoaib, M. ; Rasheed, F. ; Akhtar, J. ; Awais, M. ; Masud, S. ; Shamai, S.
Author_Institution :
Dept. of Comput. Sci., Lahore Univ. of Manage. Sci., Pakistan
fYear :
2003
fDate :
8-9 Dec. 2003
Firstpage :
371
Lastpage :
376
Abstract :
This work presents a two-tier approach through sequential application of intensity contours and formant tracks for accurate Arabic phoneme identification. The recognition system developed is based on data sets of 40 speakers for each Arabic phonetic sound. As a first step towards recognition of phonemes, the sound is sampled and then preprocessed to get formant frequencies and intensity contours. In order to automate the intensity and formant based feature extraction, a generalized regression neural network has been implemented, trained and validated on 21 input features.
Keywords :
feature extraction; learning (artificial intelligence); neural nets; speech processing; speech recognition; Arabic speech recognition; feature extraction; formant frequencies; formant tracks; generalized regression neural network; intensity contours; neural net training; phoneme identification; speaker independent speech recognition; two-tier approach; Application software; Computer science; Equations; Frequency estimation; Linear predictive coding; Neural networks; Resonant frequency; Robustness; Speech analysis; Speech recognition;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Multi Topic Conference, 2003. INMIC 2003. 7th International
Print_ISBN :
0-7803-8183-1
Type :
conf
DOI :
10.1109/INMIC.2003.1416753
Filename :
1416753
Link To Document :
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