Retraction Notice: Robustness Speaker Recognition Based on Feature Space in Clean and Noisy Condition

Author(s): Khamis A. Al-Karawi*

Journal Name: International Journal of Sensors, Wireless Communications and Control

Volume 9 , Issue 4 , 2019


Become EABM
Become Reviewer
Call for Editor

Abstract:

The article has been retracted from the journal “International Journal of Sensors, Wireless Communications and Control” as it has been found to be published as the doctoral thesis of Dr. Ahmed Hani Yousif Al-Noori entitled "Robust Speaker Recognition in Presence of Non-Trivial Environmental Noise" in 2017.

Bentham Science apologizes to its readers for any inconvenience this may have caused.

The Bentham Editorial Policy on Article Retraction can be found at https://benthamscience.com/editorial-policies-main.php.

BENTHAM SCIENCE DISCLAIMER:

It is a condition of publication that manuscripts submitted to this journal have not been published and will not be simultaneously submitted or published elsewhere. Furthermore, any data, illustration, structure or table that has been published elsewhere must be reported, and copyright permission for reproduction must be obtained. Plagiarism is strictly forbidden, and by submitting the article for publication the authors agree that the publishers have the legal right to take appropriate action against the authors, if plagiarism or fabricated information is discovered. By submitting a manuscript the authors agree that the copyright of their article is transferred to the publishers if and when the article is accepted for publication.

[1]
Al-Karawi K. Robust speaker recognition in reverberant condition-toward greater biometric security. University of Salford 2018.
[2]
Campbell JP. Speaker recognition: A tutorial. Proc IEEE 1997; 85: 1437-62.
[3]
Zhao X, Wang Y, Wang D. Robust speaker identification in noisy and reverberant conditions. IEEE/ACM Trans Audio Speech Lang Process 2014; 22(4): 836-45.
[4]
Ning PCCW, Nengheng Z, Tan L. Robust speaker recognition using denoised vocal source and vocal tract features. IEEE/ACM Trans Audio Speech Lang Process 2011; 19: 196-205.
[5]
Shin-Cheol JSJL, Soek-Pil L, Moo Young K. Hard-mask missing feature theory for robust speaker recognition. IEEE Trans Consum Electron 2011; 57: 1245-50.
[6]
May T, Van De Par S, Kohlrausch A. Noise-robust speaker recognition combining missing data techniques and universal background modeling. IEEE/ACM Trans Audio Speech Lang Process 2012; 20: 108-21.
[7]
Li Q, Huang Y. An auditory-based feature extraction algorithm for robust speaker identification under mismatched conditions. IEEE/ACM Trans Audio Speech Lang Process 2011; 19: 1791-80.
[8]
Zhao X, Shao Y, Wang D. CASA-based robust speaker identification. IEEE/ACM Trans Audio Speech Lang Process 2012; 20: 1608-16.
[9]
Zhao X, Wang D. Analyzing noise robustness of MFCC and GFCC feature in speaker identification. IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). 2013, pp. 7204-8.
[10]
Zhang DG, Wang X, Song XD. New medical image fusion approach with coding based on SCD in a wireless sensor network. J Electr Eng Technol 2015; 10: 2384-92.
[11]
Zhang D, Li G, Zheng K, Ming X, Pan ZH. An energy-balanced routing method based on forward-aware factor for wireless sensor networks. IEEE Trans Industr Inform 2014; 10: 766-73.
[12]
Plinge A, Grzeszick R, Fink GA. A bag-of-features approach to acoustic event detection. IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). 2014, pp. 3704-8.
[13]
Zhang DG, Zheng K, Zhao DX, Song XD, Wang X. Novel Quick Start (QS) method for optimization of TCP. Wirel Netw 2016; 22: 211-22.
[14]
Qi J, Wang D, Xu J, Tejedor J. Bottleneck features based on gammatone frequency cepstral coefficients. International Speech Communication Association 2013.
[15]
Qi J, Wang D, Jiang Y, Liu R. Auditory features based on gammatone filters for robust speech recognition. IEEE International Symposium on Circuits and Systems (ISCAS). 2013: pp. 305-8.
[16]
Sadjadi SO, Slaney M, Heck L. MSR Identity Toolbox v1 0: A MATLAB toolbox for speaker-recognition research. Speech and Language Processing Technical Committee Newsletter 2013.
[17]
Lei Y, Scheffer N, Ferrer L, McLaren M. A novel scheme for speaker recognition using a phonetically-aware deep neural network. IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). 2014: pp. 1695-9.
[18]
Zhang DG, Liu S, Zhang T, Liang Z. Novel unequal clustering routing protocol considering energy balancing based on network partition & distance for mobile education. J Netw Comput Appl 2017; 88: 1-9.
[19]
Patterson RD, Robinson K, Holdsworth J, McKeown DC, Zhang C, Allerhand V. Complex sounds and auditory images. Auditory Physiol Percept 1992; 83: 429-46.
[20]
Sadjadi SO, Slaney M, Heck L. MSR identity toolbox-a Matlab toolbox for speaker recognition research Microsoft Research, Conversational Systems Research Center. CSRC 2013.
[21]
Burgos W. Gammatone and MFCC features in speaker recognition. Florida Institute of Technology 2014.
[22]
Fathima R, Raseena P. Gammatone cepstral coefficient for speaker identification. Int J Adv Res Electr Electron Instrument Eng 2013; p. 2.
[23]
Zhang DG, Zhou S, Chen V, Liu V. New mixed adaptive detection algorithm for moving target with big data. J Vibroeng 2016; 18.
[24]
Zhang D, Kang X, Wang J. A novel image de-noising method based on spherical coordinates system. EURASIP J Adv Signal Process 2012; 2012: 110.
[25]
Mohammed D. Overlapped speech and music segmentation using singular spectrum analysis and random forests. Salford University 2017.
[26]
Ferrer L, McLaren M, Scheffer N, Lei Y, Graciarena M, Mitra V. A noise-robust system for NIST 2012 speaker recognition evaluation. Sri International Menlo Park Ca Speech Technology And Research Lab 2013.
[27]
Khoury E, Vesnicer B, Franco-Pedroso J, et al. The 2013 speaker recognition evaluation in mobile environment. In: 2013 International Conference on Biometrics (ICB). 2013; pp. 1-8.
[28]
Zhang D, Ge H, Zhang T, Cui YY, Liu X, Mao G. New multi-hop clustering algorithm for vehicular ad hoc networks. IEEE Trans Intell Transp Syst 2018; 1-14.
[29]
Zhang D, Wang X, Song X, Zhao D. A novel approach to mapped correlation of ID for RFID anti-collision. IEEE Trans Serv Comput 2014; 7: 741-8.


free to download

Rights & PermissionsPrintExport Cite as

Article Details

VOLUME: 9
ISSUE: 4
Year: 2019
Published on: 16 September, 2019
Page: [497 - 506]
Pages: 10
DOI: 10.2174/2210327909666181219143918

Article Metrics

PDF: 14
HTML: 2