Comparison of voice features for Arabic speech recognition

Mansour Alsulaiman, Ghulam Muhammad, Zulfiqar Ali

Research output: Contribution to conferencePaper

10 Citations (Scopus)

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 languageEnglish
Pages90-95
Number of pages6
DOIs
Publication statusPublished - 22 Dec 2011
Event2011 6th International Conference on Digital Information Management, ICDIM 2011 - var.pagings, Australia
Duration: 26 Sep 201128 Sep 2011

Conference

Conference2011 6th International Conference on Digital Information Management, ICDIM 2011
CountryAustralia
Cityvar.pagings
Period26/09/1128/09/11

Keywords

  • ANN
  • Arabic speech recognition
  • HMM
  • LBPCC
  • LPC
  • MFCC

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    Alsulaiman, M., Muhammad, G., & Ali, Z. (2011). Comparison of voice features for Arabic speech recognition. 90-95. Paper presented at 2011 6th International Conference on Digital Information Management, ICDIM 2011, var.pagings, Australia. https://doi.org/10.1109/ICDIM.2011.6093369