A Critical Review on Automatic Speaker Recognition

Nilu Singh; Alka Agrawal; Raees Ahmad Khan

doi:doi:10.11648/j.cssp.20150402.12

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A Critical Review on Automatic Speaker Recognition

Nilu Singh, Alka Agrawal, Raees Ahmad Khan

Published in Science Journal of Circuits, Systems and Signal Processing (Volume 4, Issue 2)

Received: 8 July 2015 Accepted: 14 July 2015 Published: 28 July 2015

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Abstract

Automatic Speaker Recognition (ASR) is use to recognizing persons from their voice. Since the voice of every human is not same because their vocal tract shapes, larynx sizes and other parts of a human voice production system. Automatic Speaker recognition is a procedure to automatically recognizing a speaker or who is speaking by the individual information counted in speech signal/waves. Automatic speaker recognition technique makes it possible to use the speaker's speech to verify their identity. It have many applications for example control access to services such as voice mail, voice dialing, banking by telephone, remote access to computers, telephone shopping, information services, database access services and security control for confidential information areas.

Published in	Science Journal of Circuits, Systems and Signal Processing (Volume 4, Issue 2)
DOI	10.11648/j.cssp.20150402.12
Page(s)	14-17
Creative Commons	This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.
Copyright	Copyright © The Author(s), 2015. Published by Science Publishing Group

Keywords

Speaker Recognition, Prosodic, MFCC, Pre-Processing

References

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[2]	Marcel Kockmann, Lukas Burget “Contour Modeling of Prosodic and Acoustic Features for Speaker Recognition” Speech@ FIT, Brno University, Czech Republic, pp.1-4.
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[5]	DOI: minhdo.ece.illinois.edu/teaching/speaker_recognition/speaker_recognition.html
[6]	David Michael Graeme Watts, “Speaker Identification - Prototype Development and Performance” Year 2006, pp.1-116
[7]	S Furui, “50 years of progress in speech and speaker recognition research”, ECTI Transactions on Computer and Information Technology, Vol. 1, No.2, November 2005.
[8]	Thang Wee Keong “Voice Print Analysis For Speaker Recognition” Sim Universityschool Of Science And Technology 2009, Pp. 1-75
[9]	Singh Nilu and Khan R. A. "Extraction of Prosodic Features for Speaker Recognition Technology and Voice Spectrum Analysis" International Journal of Scientific & Engineering Research (IJSER). volume 5.Issue 5 (May 2014): 600-605.
[10]	http://www.ifp.uiuc.edu/~minhdo/teaching/speaker_recognition
[11]	Utpal Bhattacharjee and Kshirod Sarmah, “SPEAKER VERIFICATION USING ACOUSTIC AND PROSODIC FEATURES” Advanced Computing: An International Journal ( ACIJ ), Vol.4, No.1, January 2013
[12]	Singh Nilu, Khan R. A., and Raj Shree. "Equal Error Rate and Audio Digitization and Sampling Rate for Speaker Recognition System." American Scientific Publishers. Volume 20, .Numbers 5-6, (May 2014): pp. 1085-1088(4).
[13]	Lee, K.-F. and Hon, H.-W., "Speaker-independent phone recognition using hidden Markov models ," . Acoustics, Speech and Signal Processing, IEEE Transactions on , vol.37, no.11, pp.1641-1648, Nov 1989.
[14]	Jayanna H S, Mahadeva Prasanna S R. "Analysis, Feature Extraction, Modeling and Testing Techniques for Speaker Recognition". IETE Tech Rev 2009;26:181-90.
[15]	X. M. Cheng, P. Y. Cheng, and L. Zhao, “A study on emotional feature analysis and recognition in speech signal,” in Proc. International Conference on Measuring Technology and Mechatronics Automation, 2009, IEEE, pp. 418-420.
[16]	Y. Linde, A. Buzo, and R.M. Gray,. "An algorithm for vector quantizer design,". IEEE Trans. Communications, vol. COM-28(1), pp. 84-96, Jan. 1980.
[17]	Nilu singh & R. A. Khan “Aritficial Intelligence and Network Security”, DESIDOC, DRDO, Metcalfe House, Delhi-110054. Bilingual International Conference on Information Technology: Yesterday, Toady, and Tomorrow, 19-21 Feburary 2015, pp. 134-138 © DESIDOC, 2015
[18]	Ayaz Keerio, Bhargav Kumar Mitra, Philip Birch, Rupert Young, and Chris Chatwin. "On Preprocessing of Speech Signals". International Journal of Signal Processing ; Vol.5 No.3 2009 pp. 216.
[19]	Nilu Singh, Khan R. A. and Raj Shree. Article: MFCC and Prosodic Feature Extraction Techniques: A Comparative Study.International Journal of Computer Applications 54(1):9-13, September 2012. Published by Foundation of Computer Science, New York, USA.
[20]	Md. Rashidul Hasan, Mustafa Jamil, Md. Golam Rabbani, Md. Saifur Rahman. "Speaker Identification using Mel Frequency cepstral coefficients". 3rd International Conference on Electrical & Computer Engineering ICECE 2004, 28-30 December 2004, Dhaka, Bangladesh.
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[25]	DOI: http://dx.doi.org/10.1155/2014/628516

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APA Style

Nilu Singh, Alka Agrawal, Raees Ahmad Khan. (2015). A Critical Review on Automatic Speaker Recognition. Science Journal of Circuits, Systems and Signal Processing, 4(2), 14-17. https://doi.org/10.11648/j.cssp.20150402.12

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ACS Style

Nilu Singh; Alka Agrawal; Raees Ahmad Khan. A Critical Review on Automatic Speaker Recognition. Sci. J. Circuits Syst. Signal Process. 2015, 4(2), 14-17. doi: 10.11648/j.cssp.20150402.12

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AMA Style

Nilu Singh, Alka Agrawal, Raees Ahmad Khan. A Critical Review on Automatic Speaker Recognition. Sci J Circuits Syst Signal Process. 2015;4(2):14-17. doi: 10.11648/j.cssp.20150402.12

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@article{10.11648/j.cssp.20150402.12,
  author = {Nilu Singh and Alka Agrawal and Raees Ahmad Khan},
  title = {A Critical Review on Automatic Speaker Recognition},
  journal = {Science Journal of Circuits, Systems and Signal Processing},
  volume = {4},
  number = {2},
  pages = {14-17},
  doi = {10.11648/j.cssp.20150402.12},
  url = {https://doi.org/10.11648/j.cssp.20150402.12},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.cssp.20150402.12},
  abstract = {Automatic Speaker Recognition (ASR) is use to recognizing persons from their voice. Since the voice of every human is not same because their vocal tract shapes, larynx sizes and other parts of a human voice production system. Automatic Speaker recognition is a procedure to automatically recognizing a speaker or who is speaking by the individual information counted in speech signal/waves. Automatic speaker recognition technique makes it possible to use the speaker's speech to verify their identity. It have many applications for example control access to services such as voice mail, voice dialing, banking by telephone, remote access to computers, telephone shopping, information services, database access services and security control for confidential information areas.},
 year = {2015}
}

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TY  - JOUR
T1  - A Critical Review on Automatic Speaker Recognition
AU  - Nilu Singh
AU  - Alka Agrawal
AU  - Raees Ahmad Khan
Y1  - 2015/07/28
PY  - 2015
N1  - https://doi.org/10.11648/j.cssp.20150402.12
DO  - 10.11648/j.cssp.20150402.12
T2  - Science Journal of Circuits, Systems and Signal Processing
JF  - Science Journal of Circuits, Systems and Signal Processing
JO  - Science Journal of Circuits, Systems and Signal Processing
SP  - 14
EP  - 17
PB  - Science Publishing Group
SN  - 2326-9073
UR  - https://doi.org/10.11648/j.cssp.20150402.12
AB  - Automatic Speaker Recognition (ASR) is use to recognizing persons from their voice. Since the voice of every human is not same because their vocal tract shapes, larynx sizes and other parts of a human voice production system. Automatic Speaker recognition is a procedure to automatically recognizing a speaker or who is speaking by the individual information counted in speech signal/waves. Automatic speaker recognition technique makes it possible to use the speaker's speech to verify their identity. It have many applications for example control access to services such as voice mail, voice dialing, banking by telephone, remote access to computers, telephone shopping, information services, database access services and security control for confidential information areas.
VL  - 4
IS  - 2
ER  -

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Author Information

Nilu Singh

SIST-DIT, Babasaheb Bhimrao Ambedkar University (Central University), Lucknow, UP, India
Alka Agrawal

Department of Computer Science, Khwaja Moinuddin Chishti Urdu, Arabi-Farsi University, Lucknow, UP, India
Raees Ahmad Khan

SIST-DIT, Babasaheb Bhimrao Ambedkar University (Central University), Lucknow, UP, India

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APA Style

Nilu Singh, Alka Agrawal, Raees Ahmad Khan. (2015). A Critical Review on Automatic Speaker Recognition. Science Journal of Circuits, Systems and Signal Processing, 4(2), 14-17. https://doi.org/10.11648/j.cssp.20150402.12

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ACS Style

Nilu Singh; Alka Agrawal; Raees Ahmad Khan. A Critical Review on Automatic Speaker Recognition. Sci. J. Circuits Syst. Signal Process. 2015, 4(2), 14-17. doi: 10.11648/j.cssp.20150402.12

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AMA Style

Nilu Singh, Alka Agrawal, Raees Ahmad Khan. A Critical Review on Automatic Speaker Recognition. Sci J Circuits Syst Signal Process. 2015;4(2):14-17. doi: 10.11648/j.cssp.20150402.12

Copy | Download

@article{10.11648/j.cssp.20150402.12,
  author = {Nilu Singh and Alka Agrawal and Raees Ahmad Khan},
  title = {A Critical Review on Automatic Speaker Recognition},
  journal = {Science Journal of Circuits, Systems and Signal Processing},
  volume = {4},
  number = {2},
  pages = {14-17},
  doi = {10.11648/j.cssp.20150402.12},
  url = {https://doi.org/10.11648/j.cssp.20150402.12},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.cssp.20150402.12},
  abstract = {Automatic Speaker Recognition (ASR) is use to recognizing persons from their voice. Since the voice of every human is not same because their vocal tract shapes, larynx sizes and other parts of a human voice production system. Automatic Speaker recognition is a procedure to automatically recognizing a speaker or who is speaking by the individual information counted in speech signal/waves. Automatic speaker recognition technique makes it possible to use the speaker's speech to verify their identity. It have many applications for example control access to services such as voice mail, voice dialing, banking by telephone, remote access to computers, telephone shopping, information services, database access services and security control for confidential information areas.},
 year = {2015}
}

Copy | Download

TY  - JOUR
T1  - A Critical Review on Automatic Speaker Recognition
AU  - Nilu Singh
AU  - Alka Agrawal
AU  - Raees Ahmad Khan
Y1  - 2015/07/28
PY  - 2015
N1  - https://doi.org/10.11648/j.cssp.20150402.12
DO  - 10.11648/j.cssp.20150402.12
T2  - Science Journal of Circuits, Systems and Signal Processing
JF  - Science Journal of Circuits, Systems and Signal Processing
JO  - Science Journal of Circuits, Systems and Signal Processing
SP  - 14
EP  - 17
PB  - Science Publishing Group
SN  - 2326-9073
UR  - https://doi.org/10.11648/j.cssp.20150402.12
AB  - Automatic Speaker Recognition (ASR) is use to recognizing persons from their voice. Since the voice of every human is not same because their vocal tract shapes, larynx sizes and other parts of a human voice production system. Automatic Speaker recognition is a procedure to automatically recognizing a speaker or who is speaking by the individual information counted in speech signal/waves. Automatic speaker recognition technique makes it possible to use the speaker's speech to verify their identity. It have many applications for example control access to services such as voice mail, voice dialing, banking by telephone, remote access to computers, telephone shopping, information services, database access services and security control for confidential information areas.
VL  - 4
IS  - 2
ER  -

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