Call for Paper - March 2023 Edition
IJCA solicits original research papers for the March 2023 Edition. Last date of manuscript submission is February 20, 2023. Read More

Text Dependent & Gender Independent Speaker Recognition Model based on Generalizations of Gamma Distribution

International Journal of Computer Applications
© 2011 by IJCA Journal
Volume 35 - Number 6
Year of Publication: 2011
K. Suri Babu
Srinivas Yarramalle
Suresh Varma Penumatsa
Nagesh Vadaparthi

Suri K Babu, Srinivas Yarramalle, Suresh Varma Penumatsa and Nagesh Vadaparthi. Article: Text Dependent & Gender Independent Speaker Recognition Model based on Generalizations of Gamma Distribution. International Journal of Computer Applications 35(6):1-4, December 2011. Full text available. BibTeX

	author = {K. Suri Babu and Srinivas Yarramalle and Suresh Varma Penumatsa and Nagesh Vadaparthi},
	title = {Article: Text Dependent & Gender Independent Speaker Recognition Model based on Generalizations of Gamma Distribution},
	journal = {International Journal of Computer Applications},
	year = {2011},
	volume = {35},
	number = {6},
	pages = {1-4},
	month = {December},
	note = {Full text available}


Speaker recognition is one of the research potential areaswith applications in biometrics and content based retrievals, it helps to identify a speaker from the speech signal. To develop an effective speaker recognition system, it is needed to have a concrete methodology of feature extraction and a mechanism to model these features, most of the models available in the literature are more focused towards the speech rather than the speaker, a novel speaker model is developed in this article using the generalized gamma mixture model, here we have considered Mel frequency cepstral coefficients (MFCC)and linear predictive coefficients (LPC).To demonstrate our model we have generated data base with 200 speakers for training the data and 50 speech samples for testing the data, the speech samples are considered for testing are segmented into frames of both long duration and short duration of five seconds,ten seconds and fifteen seconds respectively. The accuracy of the developed methodology is calculated and above 88% of accuracy is observed.


  • Lawrence R.Rabiner,(1989), A Tutorial on HMM & Selected Applications in speech Recognition, proceedings of IEEE vol-77,No-2,feb-1989,pp257-284.
  • CorneliuOctavian.D,I.Gavat,(2005),Feature Extraction Modeling &Training Strategies in continuous speech Recognition For Roman Language, EU Proceedings of IEEE Xplore,EUROCN-2005,pp-1424-1428.
  • Sunil Agarwal et al,(2010),Prosodic Feature Based Text-Dependent Speaker Recognition Using machineLearningAlgorithm,,Vol:2(10),2010,pp5150-5157.
  • .Md. RashidulHasan, et al(2004),Speaker identificationusing Mel Frequency Cepstral Coefficients,3rd International Conference on Electrical & Computer Engineering,ICECE 2004, 28-30 December 2004, Dhaka, Bangladesh.
  • Douglas.A.Reynolds,member,IEEE and Richard.C.Rose,member,IEEE, Robust text-Independent Speaker Identification Using Gaussian Mixture Speaker Models,IEEE Transactions on speech and audio processing,vol.3No.1,january1995.
  • Eddie Wong and SridhaSridharan ,(2001),Comparison of Linear Prediction Cepstrum Coefficients and Mel-Frequency Cepstrum Coefficients for Language Identification,lnternational Symposium on Intelligent Multimedia, Video and Speech Processing. May 24 2001 Hong Kong.
  • Md. AfzalHossan, SheerazMemon, Mark A Gregory “A Novel Approach for MFCC Feature Extraction” RMIT University978-1-4244-7907-8/10/$26.00 ©2010 IEEE.
  • George Almpanidis and Constantine Kotropoulos,(2006)voice activity detection with generalized gamma distribution, IEEE,ICME 2006.
  • XinGuang Li et al(2011),Speech Recognition Based on K-means clustering and neural network Ensembles,International Conference on Natural Computation,IEEEXplore Proceedings,2011,pp614-617.
  • EwaPaszek,TheGamma&chi-square Distribution,conexions,Module-M13129.
  • J.Won Shin et al(2005),Statitical modeling of Speech Based on Generalized Gamma Distribution,IEEE,Signal Processing Letters,Vol.12,No.1,March(2005),pp258-261.
  • RajeswaraRao.R.,Nagesh(2011),Source Feature Based Gender Identification System Using GMM, International Journal on computer science and Engineering,Vol:3(2),2011,pp-586-593.
  • Christos Tzagkarakis and AthanasiosMouchtaris,(2010),Robust Text-independent Speaker Identification using short testand training sessions,18thEropian signal Processing conference(EUSIPCO-2010).