Person Identification Based on Humming Using MFCC and Correlation Concept
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International Journal of Engineering Trends and Technology (IJETT) |  |
| © 2015 by IJETT Journal | ||
| Volume-23 Number-2 |
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| Year of Publication : 2015 | ||
| Authors : Nikunj Patel, Prof. Vinesh Kapadia, Prof. Kinnal Dhameliya, Dr. Ninad Bhatt |
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| DOI : 10.14445/22315381/IJETT-V23P215 |
Citation
Nikunj Patel, Prof. Vinesh Kapadia, Prof. Kinnal Dhameliya, Dr. Ninad Bhatt"Person Identification Based on Humming Using MFCC and Correlation Concept", International Journal of Engineering Trends and Technology (IJETT), V23(2),77-81 May 2015. ISSN:2231-5381. www.ijettjournal.org. published by seventh sense research group
Abstract
In this paper, an attempt is made to identify persons with the help of their hum. Normally, speech is used as an input to thebiometric system for recognition of a person, but here,instead of using speech, hum of a particular person is used for the sametask. Hum is a sound that is emerged from the nose, in which themouth is completely closed and vocal tract is directly coupled to nasal cavity. Humming is also applicable for a deaf personas well as an infant person who is not able to speak.Humming is not produced as the same way as production of normal speech, so in this paper speaker identification is referred to as person identification.Here, Mel Frequency CepstralCoefficients (MFCC) is used as a feature extraction technique and Pearson Correlation concept is used to identify the person. Identification rate is measured as a performance parameter of the system.
References
[1] HemantA. Patil, Robin Jain and Prakhar Jain, “Identification of speakers from their hum”, springer-verlag berlin heidelberg, pp. 461 - 468, 2008.
[2] Minho Jin, Jaewook Kim and Chang D. Yoo, “Humming-Based Human Verification and Identification”, International Conference on Acoustic, Speech and Signal Processing, ICASSA, pp. 1453-1456, April 2009.
[3] Hemant A. Patil and Keshab K. Parhi, “Novel Variable length Teager Energy Based features for person recognition from their hum”, International Conference on Acoustics, Speech and Signal Processing, pp. 4526-4529, March 2010.
[4] Hemant A. Patil, Maulik C. Madhavi, Rahul Jain and Alok K. Jain, “Combining Evidence from Temporal and Spectral Features for Person Recognition Using Humming”, Springer-Verlag Berlin Heidelberg, pp. 321 -328, 2012.
[5] Hemant A. Patil and Maulik C. Madhavi, “Significance of Magnitude and Phase Information via VTEO for Humming Based Biometrics”, International Conference on Biometrics, pp. 372-377, 2012.
[6] Hemant A. Patil, Maulik C Madhavi and Keshab K. Parhi , “Static and dynamic information derived from source and system features for person recognition from humming”, Springer Science+BusinessMedia, pp. 393-406, LLC 2012.
[7] Hemant A. Patil, Maulik C Madhavi and Nirav H. Chhayani, “Person Recognition using Humming, Singing and Speech”, International Conference on Asian Language Processing, pp. 149- 152, Nov. 2012.
[8] Hector Perez Meana, Advances in Audio and speech signal processing technologies and applications; Idea group publishing, pp. 377, 2007.
[9] H. Hermansky, B. A. Hanson, H. Wakita, "Perceptually based Linear Predictive Analysis of Speech", Proc. IEEE Int. Conf. on Acoustic, speech, and Signal processing, pp. 509-512, August 1985.
[10] H. Hermansky, B. A. Hanson, and H. Wakita, "Perceptually based Processing in Automatic Speech Recognition", Proc. IEEE Int. Conf. on Acoustic, speech, and Signal processing, pp. 1971 -1974, April 1986.
[11] Nidhi Desai, Prof.Kinnal Dhameliya and 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, pp. 6456-6459, May 2014.
[12] Vikrant Tomar and Hemant A. Patil, “On the development of variable length Teager energy Operator (VTEO)”, Proc. Interspeech, Brisbane, Australia, pp. 1056-1059, September 2008.
[13] Hemant A. Patil, Prakhar Kant Jain and Robin Jain, “A Novel Approach to Identifjication of Speakers from their Hum”, Seventh International Conference on Advance in pattern Recognition, pp. 167- 170, Feb. 2009
[14] W. M. Campbell, K. T. Assaleh, and C. C. Broun, “Speaker recognition with polynomial classifier”, IEEE Trans. on Speech and Audio Processing, vol. 10, no. 4, pp. 205-212, May 2002
[15] DipakHarjani, MohitaJethwani and Ms. Mani Roja, “Speaker Recognition System using MFCC and Vector Quantization Approach”, International Journal for Scientific Research & Development, Vol. 1, Issue 9, pp. 1934-1937, 2013
[16] Prof. Ch.Srinivasa Kumar and Dr. P. Mallikarjuna Rao, “Design Of An Automatic Speaker Recognition System Using MFCC, Vector Quantization And LBG Algorithm”, International Journal on Computer Science and Engineering, 2011, pp.2942-2954.
[17] Samiksha Sharma, Anupam Shukla and Pankaj Mishra, “Speech and Language Recognition using MFCC and DELTA-MFCC”, International Journal of Engineering Trends and Technology (IJETT), Volume 12, Number 9, pp. 449-452,June 2014
[18] Arjun Rajsekhar, “Real time Speaker Recognition using MFCC and VQ”, M.TechThesis,National Institute of Technology, Rourkela, India, 2008
[19] (2015), Pearson product-moment correlation coefficient, [Online]. Available: http://en.wikipedia.org/wiki/Pearson_productmoment_correlation_coef ficient
[20] (2015), Audacity Software, version 2.0.6, [Online]. Available: http://www.fosshub.com/Audacity.html/audacity-win-2.0.6.exe
Keywords
Person Identification, Humming, MFCC, Pearson Correlation, Identification rate