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Comparing spectrum estimators in speaker verification under additive noise degradation

Hanilci, C.; Kinnunen, T.; Saeidi, R.; Pohjalainen, J.; Alku, P.; Ertas, F.; Sandberg, J. and Sandsten, Maria LU (2012) 2012 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) In Acoustics, Speech and Signal Processing (ICASSP), 2012 IEEE International Conference on p.4769-4772
Abstract
Different short-term spectrum estimators for speaker verification under additive noise are considered. Conventionally, mel-frequency cepstral coefficients (MFCCs) are computed from discrete Fourier transform (DFT) spectra of windowed speech frames. Recently, linear prediction (LP) and its temporally weighted variants have been substituted as the spectrum analysis method in speech and speaker recognition. In this paper, 12 different short-term spectrum estimation methods are compared for speaker verification under additive noise contamination. Experimental results conducted on NIST 2002 SRE show that the spectrum estimation method has a large effect on recognition performance and stabilized weighted LP (SWLP) and minimum variance... (More)
Different short-term spectrum estimators for speaker verification under additive noise are considered. Conventionally, mel-frequency cepstral coefficients (MFCCs) are computed from discrete Fourier transform (DFT) spectra of windowed speech frames. Recently, linear prediction (LP) and its temporally weighted variants have been substituted as the spectrum analysis method in speech and speaker recognition. In this paper, 12 different short-term spectrum estimation methods are compared for speaker verification under additive noise contamination. Experimental results conducted on NIST 2002 SRE show that the spectrum estimation method has a large effect on recognition performance and stabilized weighted LP (SWLP) and minimum variance distortionless response (MVDR) methods yield approximately 7 % and 8 % relative improvements over the standard DFT method at -10 dB SNR level of factory and babble noises, respectively in terms of equal error rate (EER). (Less)
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author
organization
publishing date
type
Chapter in Book/Report/Conference proceeding
publication status
published
subject
keywords
speaker verification, spectrum estimation
in
Acoustics, Speech and Signal Processing (ICASSP), 2012 IEEE International Conference on
pages
4 pages
publisher
IEEE--Institute of Electrical and Electronics Engineers Inc.
conference name
2012 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
external identifiers
  • scopus:84867590081
ISSN
1520-6149
ISBN
978-1-4673-0044-5 (online)
978-1-4673-0045-2 (print)
DOI
10.1109/ICASSP.2012.6288985
language
English
LU publication?
yes
id
19390f56-2fc3-4b94-8f08-7bc18dec6457 (old id 3290081)
alternative location
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6288985
date added to LUP
2013-03-06 19:05:33
date last changed
2017-07-02 04:03:41
@inproceedings{19390f56-2fc3-4b94-8f08-7bc18dec6457,
  abstract     = {Different short-term spectrum estimators for speaker verification under additive noise are considered. Conventionally, mel-frequency cepstral coefficients (MFCCs) are computed from discrete Fourier transform (DFT) spectra of windowed speech frames. Recently, linear prediction (LP) and its temporally weighted variants have been substituted as the spectrum analysis method in speech and speaker recognition. In this paper, 12 different short-term spectrum estimation methods are compared for speaker verification under additive noise contamination. Experimental results conducted on NIST 2002 SRE show that the spectrum estimation method has a large effect on recognition performance and stabilized weighted LP (SWLP) and minimum variance distortionless response (MVDR) methods yield approximately 7 % and 8 % relative improvements over the standard DFT method at -10 dB SNR level of factory and babble noises, respectively in terms of equal error rate (EER).},
  author       = {Hanilci, C. and Kinnunen, T. and Saeidi, R. and Pohjalainen, J. and Alku, P. and Ertas, F. and Sandberg, J. and Sandsten, Maria},
  booktitle    = {Acoustics, Speech and Signal Processing (ICASSP), 2012 IEEE International Conference on},
  isbn         = {978-1-4673-0044-5 (online)},
  issn         = {1520-6149},
  keyword      = {speaker verification,spectrum estimation},
  language     = {eng},
  pages        = {4769--4772},
  publisher    = {IEEE--Institute of Electrical and Electronics Engineers Inc.},
  title        = {Comparing spectrum estimators in speaker verification under additive noise degradation},
  url          = {http://dx.doi.org/10.1109/ICASSP.2012.6288985},
  year         = {2012},
}