Abstract
Selection of the speech feature for speech recognition has been investigated for languages other than Arabic. Arabic Language has its own characteristics hence some speech features may be more suited for Arabic speech recognition than the others. In this paper, some feature extraction techniques are explored to find the features that will give the highest speech recognition rate. Our investigation in this paper showed that Mel-Frequency Cepstral Coefficients (MFCC) gave the best result. We also look at using an operator well know in image processing field to modify the way we calculate MFCC, this results in a new feature that we call LBPCC. We propose the way we use this operator. Then we conduct some experiments to test the proposed feature.
Original language | English |
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Pages | 90-95 |
Number of pages | 6 |
DOIs | |
Publication status | Published (in print/issue) - 22 Dec 2011 |
Event | 2011 6th International Conference on Digital Information Management, ICDIM 2011 - var.pagings, Australia Duration: 26 Sept 2011 → 28 Sept 2011 |
Conference
Conference | 2011 6th International Conference on Digital Information Management, ICDIM 2011 |
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Country/Territory | Australia |
City | var.pagings |
Period | 26/09/11 → 28/09/11 |
Keywords
- ANN
- Arabic speech recognition
- HMM
- LBPCC
- LPC
- MFCC