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A Novel Gender Recognition in Emotional Environment using GMM

by A. Shamim Banu, Suganthi Venkatachalam, V. Kavitha
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 115 - Number 16
Year of Publication: 2015
Authors: A. Shamim Banu, Suganthi Venkatachalam, V. Kavitha
10.5120/20233-2200

A. Shamim Banu, Suganthi Venkatachalam, V. Kavitha . A Novel Gender Recognition in Emotional Environment using GMM. International Journal of Computer Applications. 115, 16 ( April 2015), 11-15. DOI=10.5120/20233-2200

@article{ 10.5120/20233-2200,
author = { A. Shamim Banu, Suganthi Venkatachalam, V. Kavitha },
title = { A Novel Gender Recognition in Emotional Environment using GMM },
journal = { International Journal of Computer Applications },
issue_date = { April 2015 },
volume = { 115 },
number = { 16 },
month = { April },
year = { 2015 },
issn = { 0975-8887 },
pages = { 11-15 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume115/number16/20233-2200/ },
doi = { 10.5120/20233-2200 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:54:58.996172+05:30
%A A. Shamim Banu
%A Suganthi Venkatachalam
%A V. Kavitha
%T A Novel Gender Recognition in Emotional Environment using GMM
%J International Journal of Computer Applications
%@ 0975-8887
%V 115
%N 16
%P 11-15
%D 2015
%I Foundation of Computer Science (FCS), NY, USA
Abstract

The emotional speech is considered as a prominent aspect in human speech communication. Emotional Speech based gender recognition has its efficacy in real world applications like biometrics, human computer related fields, voice synthesis etc. The goal of gender recognition is to extract the information from speech signal depending on speaker identity. The recognition of the gender of the speaker in emotional state is main premise of this proposed work. Both prosodic features and spectral domain features are used. The parameters of prosodic features include pitch, energy and formant; spatial features include Mel Frequency Cepstral Co efficient (MFCC). Gaussian Mixture Model is used as classifier to train and classify the gender from the features extracted from Berlin database. The accuracy of the proposed techniques is measured using metrics like Sensitivity, Specificity and likelihood ratio.

References
  1. Y. Zeng, Z. Wu, T. Falk, and W. Y. Chan. "Robust GMM based gender classification using pitch and RASTA-PLP parameters of speech". In Proc. 5th. IEEE Int. Conf. Machine Learning and Cybernetics, pages 3376–3379. Dalian, China, 2006.
  2. D. Ververidis and C. Kotropoulos. Automatic speech classification to five emotional states based on gender information. In Proc. of 12th European Signal Processing Conf. , pages 341–344. Vienna, Austria, September 2004.
  3. Chung-Hsien Wu and Wei-Bin Liang "Emotion Recognition of Affective Speech Based on Multiple Classifiers Using Acoustic-Prosodic Information and Semantic Labels. IEEE Transaction on affective computing ,Issue no 1 jan-march 2011
  4. D. Ververidis and C. Kotropoulos. Automatic speech classification to five emotional states based on gender information. In Proc. of 12th European Signal Processing Conf. , pages 341–344. Vienna, Austria, September 2004.
  5. K. Meena, , Subramaniam, Muthusamy and Gomathy, "Gender Classification in Speech Recognition using Fuzzy Logic and Neural Network" The International Arab Journal of Information Technology, Vol. 10, No. 5, September 2013
  6. Rajeshwara Rao et al " Source Feature Based Gende Identification System Using GMM" International Journal on Computer Science and Engineering (IJCSE), ISSN: 0975-3397, Vol 3 No. 2 Feb
  7. DB- Berlin Emotional Database http://emodb. bilderbar. info
  8. L. R. Rabiner, M. J. Cheng, A. E. Rosenberg, and C. A. McGonegal. "A comparative performance study of several pitch detection algorithms". IEEE Transactions on Audio,Signal, and Speech Processing 24, 399-417 1976
  9. Rakesh K. , Dutta S. , and Shama K. , "Gender Recognition using Speech Processing Techniques" in LABVIEW," International Journal of Advances in Engineering & Technology, vol. 1, no. 2, pp. 51-63, 2011
  10. Roberts, William J. J. , Willmore ". Automatic speaker recognition using Gaussian mixture model" Information, Decision and Control, 1999. IDC 99. Proceedings. 1999, 10. 1109/IDC. 1999. 754201, pages 465 – 470. ISBN:-7803-5256-4.
  11. Juan-Luis García Zapata, Juan Carlos Díaz Martín,, Pedro Gómez Vilda, "Fast formant estimation by complex analysis of LPC coefficients" Proceedings/Eusipco, Eusipco 2004, pages 737-740.
  12. Lawrence R. Rabiner," On the Use of Autocorelation Analysis for Pitch Detection" IEEE transactions on acoustics, speech, and signal processing, vol. asp-25, no. 1, february 1977
  13. Jakub Karwan, Khalid Saeed, "A New Algorithm for Speech and Gender Recognition on the Basis of Voiced Parts of Speech" Communications in Computer and Information Science Volume 245, 2011, pp 113-120.
  14. Bageshree V. Sathe-Pathak, Ashish R. Panat "Extraction of Pitch and Formants and its Analysis to identify 3 different emotional states of a person identify 3 different emotional states of a person "ISSN (Online): 1694-0814'
Index Terms

Computer Science
Information Sciences

Keywords

Gender recognition GMM short time energy formant.

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