Speaker Recognition using Gaussian Mixture Model

International Journal of Computer & Organization Trends  (IJCOT)          
© 2016 by IJCOT Journal
Volume - 6 Issue - 2
Year of Publication : 2016
Authors : H.AaliyaAmreen, K.KhadarNawas
DOI : 10.14445/22492593/IJCOT-V33P310


H.AaliyaAmreen, K.KhadarNawas"Speaker Recognition using Gaussian Mixture Model", International Journal of Computer & organization Trends (IJCOT), V6(2):48-53 Mar - Apr 2016, ISSN:2249-2593, www.ijcotjournal.org. Published by Seventh Sense Research Group.

Abstract Speaker recognition is a term which is most popular in biometric recognition technique that tends to identify and verify a speaker from his/her speech data. Speaker recognition system uses mechanism to recognize the speaker by using the speaker’s speech signal. It is mainly useful in applications where security is the main and important one. Generally, speech information are recorded though the air microphone and these speech information collected from various speakers are used as input for the speaker recognition system as they are prone to environmental background noise, the performance is enhanced by integrating an additional speech signal collected through a throat microphone along with speech signal collected from standard air microphone. The resulting signal is very similar to normal speech, and is not affected by environmental background noise. This paper is mainly focused on extraction of the Mel frequency Cepstral Coefficients (MFCC) feature from an air speech signal and throat speech signal to built Gaussian Mixture Model(GMM) based closed-set text independent speaker recognition systems and to depict the result based on identification.


[1] Jia-Ching Wang,Yu-Hao Chin,Wen-Chi Hsieh,Chang-Hong Lin,Ying-Ren Chen,Siahaan.E, “Speaker Identification With Whispered Speech for the Access Control System”, Automation Science and Engineering, IEEE Transactions , vol 12,no 4, pp. 1191-1199, 2015.
[2] Kawthar Yasmine Zergat and Abderrahmane Amrouche, “New Scheme based on GMM-PCA-SVM Modeling for Automatic Speaker Recognition”, International Journal of Speech Technology, vol 17, no 4, pp. 373-381, 2014.
[3] Maxim Sidorov, Alexander Schmitt, Sergey Zablotskiy and Wolfgang Minker, “Survey of Automatic Speaker Identification Methods”, Proceedings of the Ninth International Conference on Intelligent Environments, pp. 236-239, 2013.
[4] Cherifa S. and Messaoud R,“New Technique to use the GMM in Speaker Recognition System (SRS)”, International Conference on Computer Applications Technology, pp. 1-5, 2013.
[5] Seiichi Nakagawa, Longbiao Wang and Shinji Ohtsuka, “Speaker Identification and Verification by Combining MFCC and Phase Information” IEEE Transactions on Audio, Speech and Language Processing, vol. 20, no. 4, 2012.
[6] Rishiraj Mukherjee, Tanmoy Islam and Ravi Sankar, “Text Dependent Speaker Recognition using Shifted MFCC”, Proceedings of IEEE Southeast Conference, pp. 1-4, 2012.
[7] Homayoon Beigi, “Fundamentals of Speaker Recognition” Springer Publications, pp. 75-84, 2011.
[8] Douglas A. Reynolds, Thomas F. Quatieri, and Robert B. Dunn, “Speaker Verification Using Adapted Gaussian Mixture Models”, Digital Signal Processing, vol. 10, no. 1–3, July 2010.
[9] Tomi Kinnunen and Haizhou Li, “An Overview of Text- Independent Speaker Recognition: From Features to Supervectors”, Elsevier Journal of Speech Communication, vol. 52, no 1, pp. 12-40, 2010.
[10] Marcos Faundez-Zanuy and Enric Monte-Moreno, “State-of-the-Art in Speaker Recognition” IEEE Aerospace and Electronic Systems Magazine, vol. 20, no 5, pp. 7-12, May 2005.
[11] Joseph P. Campbell Jr., “Speaker Recognition: A Tutorial”, Proceedings of the IEEE, vol. 85, no 9, pp. 1437-1462, September 1997.
[12] Robin King, “New Challenges in Automatic Speech Recognition and Speech Understanding”, IEEE TENCON, Conference on Speech and Image Technologies for Computing and Telecommunication, pp. 287-294, 1997.
[13] Weng, Z., Li, L., & Guo, D, “Speaker recognition using weighted dynamic MFCC based on GMM”, Proceedings - 2010 International Conference on Anti-Counterfeiting, Security and Identification, pp.285–288, 2010.
[14] M. Arun Marx, G.Vinoth, A. Shahina, A. Nayeemulla Khan, “Throat Microphone Speech Corpus for Speaker Recognition”,MES Journal of Technology and Management,pp.16-20,2008.

Speaker Recognition, GMM, MFCC, Throat Microphone.