Speech Denoinsing and Arabic Speaker Recognition System Using Subband Approach


(*) Corresponding author


Authors' affiliations


DOI's assignment:
the author of the article can submit here a request for assignment of a DOI number to this resource!
Cost of the service: euros 10,00 (for a DOI)

Abstract


This paper proposes an efficient speech recognition method for Arabic language. A Hidden Markov Models based speech recognition system was designed and tested with automatic Arabic word recognition. The system is an isolated whole word speech recognizer and it was implemented as both a wideband speech signal and a subbands spectral recognition modes. We particularly discuss the selection of the most critical subbands for the speaker recognition task and the choice of an optimal division of the frequency domain. An appropriate selection of the most critical subbands shows that very good performances are still obtained with only half of the frequency domain, the strategy of decision rests on the individual decisions of recognizers in each subband. This recognition system achieved a 89.5% correct word recognition in the wideband mode, and 95.25% in subbands mode. A comparison between the various variants of analysis will be made to observe their performances.
Copyright © 2016 Praise Worthy Prize - All rights reserved.

Keywords


Arabic Words; Recognition; Speech; Subband; HMMs

Full Text:

PDF


References


E. Hagos, Implementation of an Isolated Word Recognition System, Master thesis, University of Petroleum and Minerals, Dhahran, Saudi Arabia, 1985.

W. Abdulah, M. Abdul-Karim, Real-time spoken arabic recognizer, International Journal of Electronics 59 (5) (1984) 645–648.

Y. A. Alotaibi, Investigating spoken Arabic digits in speech recognition setting, Information Sciences, Volume 173 (1-3): 115-139 (2005).

H. Bourlard, S. Dupont, Subband-based speech recognition.In Proc. IEEE Intl. Conf. on Acoustics, Speech and Signal Processing, PP 1251-1254, Munich, Germany, April 1997.

L. Besacier, J. F. Bonastre,., Subband approach for automatic speaker recognition: optimal division of the frequency domain, In Audio-and Video-based Biometric Person Authentication, Bigün, et. Al; Eds., Springer LNCS 1206, 1997.

L. Besacier, J. F. Bonastre, Frame Pruning for Speaker Recognition. Proc. IEEE International Conference on Acoustics Speech and Signal Processing. 12-15 May 1998. Seattle (USA).

K. Kirchhoff et al., Novel approaches to Arabic speech recognition, final report from the JHU summer workshop 2002, Tech. Rep., John-Hopkins University, 2002.

S. Tibrewala, H. Hermansky, Subband-based recognition of noisy speech, In PROC. IEEE Intl. Conf. on Acoustics, Speech and Signal Processing, pp 1255-1258, Munich, Germany, April 1997.

D. O'Shaughnessy. Speech communication: Human and machine, IEEE Press, New York, second edition, 2000.

S. J. Young, P.C. Woodland, W. J. Byrne, HTK Reference Manual, for htk version 3.1, December 2001.

M.A. Khawaja, N.G. Haider, Acoustic Analysis of Phonetics of Arabic Script Sindhi Language to evaluate Vowel-Consonant Segmentation, Journal of Independent Studies and Research (JISR)Volume 2, Number 2, July 2004

Z. Sakka, A. Kachouri, A. Benaissa, M. Samet, Automatic speech recognition using cepstral and itakura-saito distances for vocal command, Third International Conference on Systems, Signals & Devices, SSD’2005, 21-24 Mars 2005, Sousse - Tunisie.

N.G. Haider, Transforms for Speech Recognition, Journal of Independent Studies and Research (JISR)Volume 3, Number 1, January 2005.

Z. Sakka, A. Kachouri , M. Samet, Speech recognition with hmm models for cochlear prostheses" 2004 IEEE International Conference on Industrial Technology, IEEE-ICIT'2004, 8-10 Décembre 2004, Hammamet - Tunisie.

L. Souici, M. Sellami, A hybrid neuro-symbolic approach for arabic handwritten word recognition, JACIII, Journal of Advanced Computational Intelligence and Intelligent Informatics, Vol. 10, N°1, January 2006.

T. Farah, L. Souici,, M. Sellami, Classifiers combination and syntax analysis for arabic literal amount recognition, Engineering Applications of Artificial Intelligence, Volume 19, Issue 1, February 2006.

J. H. Husøy and T. Gjerde, Computationally efficient subband coding of ECG signals Medical Engineering and Physics, Mars 1996.

P.P. Vaidyanathan, Multirate Systems and Filter Banks. Englewood Cliffs, Prentice Hall, 1993.


Refbacks

  • There are currently no refbacks.


Please send any question about this web site to info@praiseworthyprize.com
Copyright © 2005-2024 Praise Worthy Prize