DocumentCode :
2602214
Title :
A Novel Approach to Very Fast and Noise Robust,Isolated Word Speech Recognition
Author :
Halavati, Ramin ; Shouraki, Saeed Bagheri ; Tajik, Hossein ; Cholakian, Arpineh ; Razaghpour, Mina
Author_Institution :
Dept. of Comput. Eng., Sharif Univ. of Technol., Tehran
Volume :
3
fYear :
0
fDate :
0-0 0
Firstpage :
190
Lastpage :
193
Abstract :
A novel very light weight approach to isolated word speech recognition is introduced. The approach uses a new simplistic feature set and a neural network recognition system. The algorithm´s main processing requirements are FFT computation and a simple neural network comparison, making the method a suitable solution for low price embedded devices. The proposed method is tested on single speaker and multiple speaker test sets and the results are compared with a widely used speech recognition approach, presenting very fast recognition and quite good recognition rate
Keywords :
fast Fourier transforms; neural nets; speech recognition; FFT computation; fast Fourier transform; isolated word speech recognition; multiple speaker test; neural network recognition; noise robust speech recognition; simplistic feature set; Embedded computing; Feature extraction; Frequency; Hidden Markov models; Humans; Neural networks; Noise robustness; Spectrogram; Speech recognition; Testing;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Pattern Recognition, 2006. ICPR 2006. 18th International Conference on
Conference_Location :
Hong Kong
ISSN :
1051-4651
Print_ISBN :
0-7695-2521-0
Type :
conf
DOI :
10.1109/ICPR.2006.133
Filename :
1699499
Link To Document :
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