Multilingual Person Identification

  IJETT-book-cover  International Journal of Engineering Trends and Technology (IJETT)          
© 2014 by IJETT Journal
Volume-10 Number-1                          
Year of Publication : 2014
Authors : Praveen Singh Rathore , Dr. Neeta Tripathi


Praveen Singh Rathore , Dr. Neeta Tripathi. "Multilingual Person Identification", International Journal of Engineering Trends and Technology (IJETT), V10(1),1-3 April 2014. ISSN:2231-5381. published by seventh sense research group


Speech conveys the word being spoken and information about the speakers. The speaker recognition is divided into two parts speaker identification and speaker verification. Present paper explores the idea to identify multi-lingual person by basic features. In the present approach the speech signals are recorded and basic features pitch and formant frequency has been calculated. The neural network approach is use for training of system. Here we consider two languages Hindi and Marathi including male and female. We base our approach on multilingual person identification using basic features.


[1] B. S. Atal, “Automatic Recognition of Speakers from Their Voices,” Proceedings of the IEEE vol. 64, pp. 460-475, 1976.
[2] G. R. Doddington, “Speaker Recognition-Identifying People by their Voices,” Proceedings of the IEEE, vol. 73, No. 11, pp 1651-1664, 1985.
[3] J. Campbell, “Speaker recognition: A tutorial”, Proceedings of the IEEE, vol.85, pp 1437–1462, 1997.
[4] Lawrence Rabiner and Biing-Hwang Juang, “Fundamental of Speech Recognition”, Prentice-Hall, Englewood Cliffs, N.J., 1993.
[5] U.Shrawankar, V.Thakre, “Feature extraction for a speech recognition system in noisy environment: A study”, ICCEA, vol.1, pp 358-361,March 2010.
[6] Utpal Bhattacharjee and Kshirod Sarmah, “Speaker verification using acoustic and prosodic features Advance Computing International Journal (ACIJ), Vol.4, No.1, January 2013.
[7] E.E. Shriberg, “Higher Level Features in Speaker Recognition”, Springer, vol 43. Computer science artificial intelligence, pp 241-259, 2007.
[8] Herve Bourlard, John Dines, Mathew Magimai, Doss, “Current trends in multilingual speech processing”, Sadhana, vol. 36, Part 5, pp. 885-915,October 2011.
[9] Gurpreet kaur,Harjeet kour, “Multi Lingual Speaker Identification on Foreign Languages Using Artificial Neural Network with Clustering”. International general of Computer Science and Software Engineering, volume 3, Issue 5, May 2013.
[10] Suzan A. Mahmood, Loay E. George, “Speaker Identification using back propagation neural network”. (JZS) Journal of Zankoy Sulaimani, vol.10(1), pp 61-66, December 2008.
[11] Sanjay Decate, Anupam Shukla,“Speaker Recognition Based on Multilingual Speech Features using Neural Network Models”,Oriental COCOSDA,2010.
[12] Lawrence R. Rabiner, Michael J. cheng, Aaron Rosenberg, Carol A. Mcgonegal, “A comparative performance study of several pitch detection algorithms” IEEE transactions on acoustics, speech, and signal processing, vol. assp-24,no. 5, pp399-417,October 1976.
[13] Biljana Prica and Sinisa Ili, “Recognition of Vowels in Continuous Speech by Using Formants,ELEC. ENERG. vol. 23, no. 3, pp379-393, December 2010.
[14] Hui Lin, Jui ting Huang, Yun hsuan Sung, “Recognition of multilingual speech in mobile applications”.Acoustic speech and signal processing(ICASSP),pp 4881-4884,2012.

Pitch, formant frequency, multi-lingual identification and neural network.