CFP last date
20 December 2024
Call for Paper
January Edition
IJCA solicits high quality original research papers for the upcoming January edition of the journal. The last date of research paper submission is 20 December 2024

Submit your paper
Know more
The week's pick
Responsive image
Improved Shuffled Frog Leaping Algorithm with Self-Adaptive Shuffling for Fuzzy Logic PD+G Controller Optimization in Robotic Manipulators

Duc Hoang Nguyen
Random Articles
Reseach Article

Article:Automatic Gender Identification for Hindi Speech Recognition

by D.Shakina Deiv, Gaurav, Mahua Bhattacharya
journal cover thumbnail

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 31 - Number 5
Year of Publication: 2011
Authors: D.Shakina Deiv, Gaurav, Mahua Bhattacharya
10.5120/3817-5277

D.Shakina Deiv, Gaurav, Mahua Bhattacharya . Article:Automatic Gender Identification for Hindi Speech Recognition. International Journal of Computer Applications. 31, 5 ( October 2011), 1-8. DOI=10.5120/3817-5277

@article{ 10.5120/3817-5277,
author = { D.Shakina Deiv, Gaurav, Mahua Bhattacharya },
title = { Article:Automatic Gender Identification for Hindi Speech Recognition },
journal = { International Journal of Computer Applications },
issue_date = { October 2011 },
volume = { 31 },
number = { 5 },
month = { October },
year = { 2011 },
issn = { 0975-8887 },
pages = { 1-8 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume31/number5/3817-5277/ },
doi = { 10.5120/3817-5277 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:17:18.805334+05:30
%A D.Shakina Deiv
%A Gaurav
%A Mahua Bhattacharya
%T Article:Automatic Gender Identification for Hindi Speech Recognition
%J International Journal of Computer Applications
%@ 0975-8887
%V 31
%N 5
%P 1-8
%D 2011
%I Foundation of Computer Science (FCS), NY, USA
Abstract

This paper presents the preliminary work done towards the development of a Gender Recognition System that can be incorporated into the Hindi Automatic Speech Recognition (ASR) System. Gender Recognition (GR) can help in the development of speaker-independent speech recognition systems. This paper presents a general approach to identifying feature vectors that effectively distinguish gender of a speaker from Hindi phoneme utterances. 10 vowels and 5 nasals of the Hindi language were studied for their effectiveness in identifying gender of the speaker. All the 10 vowel Phonemes performed well, while b] bZ] Å] ,] ,s] vks and vkS showed excellent gender distinction performance. All five nasals ³] ´] .k] u and e which were tested, showed a recognition accuracy of almost 100%. The Mel Frequency Cepstral Coefficients (MFCC) are widely used in ASR. The choice of MFCC as features in Gender Recognition will avoid additional computation. The effect of the MFCC feature vector dimension on the GR accuracy was studied and the findings presented.

References
  1. Kumar, K. and Aggarwal, R. K.2011 Hindi Speech Recognition System using HTK. Int. J. of Computing and Business Research, ISSN (Online) : 2229-6166, Volume 2, Issue 2.
  2. Sedaaghi, M. H. 2009 A Comparative Study of Gender and Age Classification in Speech Signals. Iranian Journal of Electrical & Engineering. Vol. 5, No. 1
  3. Childers, D. G., Wu, K. and Hicks, D. M. 1987. Factors in voice quality: acoustic features related to gender. In Proc. IEEE Int. Conf. Acoustics, Speech, and Signal Processing, volume 1, pages 293–296.
  4. Harb, H. and Chen, L. 2006 Gender Identification using a general Audio Classifier. Multimedia Tools and Applications, volume 34, No. 3, 375-395.
  5. Abdulla, W. and Kasabov, N. 2001 . Improving speech recognition performance through gender separation. In Proc. Int. Conf. Artificial Neural Networks and Expert Systems (ANNES), pages 218–222, Dunedin, New Zealand.
  6. Wu, K. and Childers, D.G. 1991 Gender recognition from speech. Part I: Coarse analysis. J.Acoust. Soc. of Am., 90(4):1828–1840.
  7. Pronobis, M. and Doss, M.M. Analysis of F0 and Cepstral Features for Robust Automatic Gender Recognition. https://docs.google.com
  8. Singh, S. and. Rajan, E.G. 2011 Vector Quantization Approach for Speaker Recognition using MFCC and Inverted MFCC. Int. J. of Computer Applications (0975 – 8887). Volume 17, No.1.
  9. Feld,M., Burkhardt, F. and Muller, C. 2010 Automatic Speaker Age and Gender Recognition in the Car for Tailoring Dialog and Mobile Services, INTERSPEECH- 2010, 2834-2837
  10. Ting, H., Yingchun, Y. and Zhaohui, W. 2006 Combining MFCC and Pitch to Enhance the Performance of the Gender Recognition Proc. Int. Conf. on Signal processing.
  11. Rajeshwara Rao, R. and Prasad, A. 2011 Glottal Excitation Feature based Gender Identification System using Ergodic HMM. Int. J. of Computer Applications (0975 – 8887). Volume 17, No.3, pages 0975 – 8887.
  12. Metze,F., Ajmera, J., Englert,R., Bub,U., Burkhardt, F., Stegmann,J., Muller, C. , Huber,R., .Andrassy, B.,. Bauer, J. G and Little, B. 2007 Comparison of four approaches to age and gender recognition for telephone applications. In Proc. 2007 IEEE Int. Conf. Acoustics, Speech and Signal Processing, volume 4, pages 1089–1092. Honolulu
  13. Sedaaghi, M. H 2008 Gender Classification in Emotional Speech. Speech Recognition, Technologies and Applications, pp. 550, www.intechweb.org
  14. Milan Sigmund 2008 Gender Distinction using Short Segments of Speech Signal. Int. J. of Computer Science and Network Security, Vol.8, No.10.
  15. Milan Sigmund 2008 Automatic Speaker Recognition by Speech Signal. Frontiers in Robotics, Automation and Control.
  16. Gurgen FS, Fan T and Vonwiller J.1994 On the Analysis of Phoneme based features for Gender Identification with Neural Networks. SST 1994. Australian Speech Science and Technology Association Inc.
  17. Hasan, M.R., Jamil, M, Rabbani, M.G. and Rahman, M. S.2004 Speaker Identification using Mel frequency Cepstral Coefficients. Proc.3rd Int. Con. on Electrical & Computer Engineering, Dhaka, Bangladesh.
  18. The HTK Book for HTK Version 3.4, 2009 Cambridge University Engineering Department.
Index Terms

Computer Science
Information Sciences

Keywords

Gender Recognition Mel-Frequency Cepstral Coefficients Hindi Phonemes

Powered by PhDFocusTM