Voice recognition Using back propagation algorithm in neural networks

International Journal of Computer Trends and Technology (IJCTT)          
© 2015 by IJCTT Journal
Volume-23 Number-3
Year of Publication : 2015
Authors : Abdelmajid Hassan Mansour, Gafar Zen Alabdeen Salh, Hozayfa Hayder Zeen Alabdeen
DOI :  10.14445/22312803/IJCTT-V23P128


Abdelmajid Hassan Mansour, Gafar Zen Alabdeen Salh, Hozayfa Hayder Zeen Alabdeen "Voice recognition Using back propagation algorithm in neural networks". International Journal of Computer Trends and Technology (IJCTT) V23(3):132-139, May 2015. ISSN:2231-2803. www.ijcttjournal.org. Published by Seventh Sense Research Group.

Abstract -
One of the most terms in the biometric technologies is the voice recognition. It’s used to provide an authentication to any system on basis of the voice features instead of images. This research aims to build a system of voice recognition using back propagation algorithm in neural networks, by comparing the voice signal of the speaker with recorded voice signals in the database, and extracting the main features of the voice signal using Mel-frequency cepstral coefficients, which is one of the most important factors in achieving high recognition accuracy.

[1] Dr. Kavitha. R, Nachammai. N, Ranjani. R, Shifali. J, Speech Based Voice Recognition System for Natural Language Processing, (IJCSIT) International Journal of Computer Science and Information Technologies, Vol. 5 (4), 2014, ISSN: 0975-9646, pp. 5301-5305
[2] Debnath Bhattacharyya, Rahul Ranjan, Farkhod Alisherov A. and Minkyu Choi, ?Biometric Authentication: A Reviewgy Vol. 2, No. 3, September, 2009.
[3] Judith A. Markowitz, ?Voice Biometrics, September 2000/Vol. 43, No. 9, Communications of the ACM.
[4] Shumaila Iqbal, Tahira Mahboob and Malik Sikandar Hayat Khiyal, ?Voice Recognition using HMM with MFCC for Secure ATM, IJCSI International Journal of Computer Science Issues, Vol. 8, Issue 6, No 3, November 2011, ISSN (Online): 1694-0814, pp. 297-303.
[5] N. Revathy, T.Guhan, ?FACE RECOGNITION SYSTEM USING BACK PROPAGATION ARTIFICIAL NEURAL NETWORKS, International Journal of Advanced Engineering Technology E-ISSN 0976-3945, IJAET/Vol.III/ Issue I/January-March, 2012, pp. 321-324.
[6] Jayanta Kumar Basu, Debnath Bhattacharyya, Tai-hoon Kim2, Use of Artificial Neural Network in Pattern Recognition, International Journal of Software Engineering and Its Applications, Vol. 4, No. 2, April 2010, pp. 23-34.
[7] N.AYSHWARYA, G.LOGESHWARI, G.S.ANANDHA MALA, ?FEED FORWARD BACK PROPAGATION NEURAL NETWORK FOR SPEAKER INDEPENDENT SPEECH RECOGNITION, International Journal of Industrial Electronics and Electrical Engineering, ISSN: 2347-6982 Volume-2, Issue-8, Aug.-2014, pp. 36- 39.
[8] Siddhant C. Joshi, Dr. A.N.Cheeran, ?MATLAB Based Back- Propagation Neural Network for Automatic Speech Recognition, International Journal of Advanced Research in Electrical, Electronics and Instrumentation Engineering, ISSN (Online): 2278 – 8875, Vol. 3, Issue 7, July 2014, pp. 10498- 10504.
[9] Md. Ali Hossain, Md. Mijanur Rahman, Uzzal Kumar Prodhan, Md. Farukuzzaman Khan, ?Implementation Of Back-Propagation Neural Network For Isolated Bangla Speech Recognition, International Journal of Information Sciences and Techniques (IJIST) Vol.3, No.4, July 2013, pp. 1-9.
[10] Lindasalwa Muda, Mumtaj Begam and I. Elamvazuthi, Voice Recognition Algorithms using Mel Frequency Cepstral Coefficient (MFCC) and Dynamic Time Warping (DTW) Techniques, JOURNAL OF COMPUTING, VOLUME 2, ISSUE 3, MARCH 2010, ISSN 2151-9617, pp. 138 -143.
[11] Md. Akkas Ali, Manwar Hossain and Mohammad Nuruzzaman Bhuiyan, Automatic Speech Recognition Technique for Bangla Words, International Journal of Advanced Science and Technology Vol. 50, January, 2013, pp. 51-60.
[12] MarutiLimkar, RamaRao & VidyaSagvekar, ?Isolated Digit Recognition Using MFCC AND DTW, International Journal on Advanced Electrical and Electronics Engineering, (IJAEEE), ISSN (Print): 2278-8948, Volume-1, Issue-1, 2012, pp. 59-64.
[13] M.A.Anusuya, S.K.Katti, Classification Techniques used in Speech Recognition Applications: A Review -– Int. J. Comp. Tech. Appl., July-August 2011 -Vol 2 (4), 910-954.
[14] Ms. Savitha and S Upadhya, Digit Recognizer Using Single and Average Template Matching Techniques, International Journal of Emerging Technologies in Computational and Applied Sciences, 3(3), Dec.12-Feb.13, ISSN (Online): 2279-0055, pp. 357-362.
[15] Om Prakash Prabhakar, Navneet Kumar Sahu, A Survey On: Voice Command Recognition Technique, International Journal of Advanced Research in Computer Science and Software Engineering, Volume 3, Issue 5, May 2013 ISSN: 2277 128X, pp. 576-585.
[16] Sahil Verma, Tarun Gulati, Rohit Lamba, RECOGNIZING VOICE FOR NUMERICS USING MFCC AND DTW International Journal of Application or Innovation in Engineering & Management (IJAIEM), Volume 2, Issue 5, May 2013 ISSN 2319 – 4847, pp. 127 -130.
[17] Nidhi Desai 1, Prof.Kinnal Dhameliya2, Prof. Vijayendra Desai, ?Recognizing voice commands for robot using MFCC and DTW, International Journal of Advanced Research in Computer and Communication Engineering Vol. 3, Issue 5, May 2014, ISSN (Online), 2278-1021, pp. 6456 6459.

Voice Recognition, Feature Extraction, Feature matching, voice signal. Back propagation, Mel-frequency Cepstral Coefficients “MFCC”.