Evaluation of kernel methods for speaker verification and identification

Vincent Wan; Steve Renals

doi:10.1109/ICASSP.2002.5743806

Evaluation of kernel methods for speaker verification and identification

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract / Description of output

Support vector machines are evaluated on speaker verification and speaker identification tasks. We compare the polynomial kernel, the Fisher kernel, a likelihood ratio kernel and the pair hidden Markov model kernel with baseline systems based on a discriminative polynomial classifier and generative Gaussian mixture model classifiers. Simulations were carried out on the YOHO database and some promising results were obtained.

Original language	English
Title of host publication	Proceedings of the 2002 IEEE International Conference on Acoustics, Speech, and Signal Processing
Subtitle of host publication	ICASSP 2002
Publisher	Institute of Electrical and Electronics Engineers (IEEE)
Pages	669-672
ISBN (Print)	0-7803-7402-9
DOIs	https://doi.org/10.1109/ICASSP.2002.5743806
Publication status	Published - May 2002
Event	2002 IEEE International Conference on Acoustics, Speech, and Signal Processing - Orlando, FL, United States Duration: 13 May 2002 → 17 May 2002

Conference

Conference	2002 IEEE International Conference on Acoustics, Speech, and Signal Processing
Country/Territory	United States
City	Orlando, FL
Period	13/05/02 → 17/05/02

Access to Document

10.1109/ICASSP.2002.5743806

http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=5743806

Cite this

@inproceedings{45d5af26fd374f118ef27f5185a8554e,

title = "Evaluation of kernel methods for speaker verification and identification",

abstract = "Support vector machines are evaluated on speaker verification and speaker identification tasks. We compare the polynomial kernel, the Fisher kernel, a likelihood ratio kernel and the pair hidden Markov model kernel with baseline systems based on a discriminative polynomial classifier and generative Gaussian mixture model classifiers. Simulations were carried out on the YOHO database and some promising results were obtained.",

author = "Vincent Wan and Steve Renals",

year = "2002",

month = may,

doi = "10.1109/ICASSP.2002.5743806",

language = "English",

isbn = "0-7803-7402-9",

pages = "669--672",

booktitle = "Proceedings of the 2002 IEEE International Conference on Acoustics, Speech, and Signal Processing",

publisher = "Institute of Electrical and Electronics Engineers (IEEE)",

address = "United States",

note = "2002 IEEE International Conference on Acoustics, Speech, and Signal Processing ; Conference date: 13-05-2002 Through 17-05-2002",

}

Wan, V & Renals, S 2002, Evaluation of kernel methods for speaker verification and identification. in Proceedings of the 2002 IEEE International Conference on Acoustics, Speech, and Signal Processing: ICASSP 2002. Institute of Electrical and Electronics Engineers (IEEE), pp. 669-672, 2002 IEEE International Conference on Acoustics, Speech, and Signal Processing, Orlando, FL, United States, 13/05/02. https://doi.org/10.1109/ICASSP.2002.5743806

Evaluation of kernel methods for speaker verification and identification. / Wan, Vincent; Renals, Steve.
Proceedings of the 2002 IEEE International Conference on Acoustics, Speech, and Signal Processing: ICASSP 2002. Institute of Electrical and Electronics Engineers (IEEE), 2002. p. 669-672.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

TY - GEN

T1 - Evaluation of kernel methods for speaker verification and identification

AU - Wan, Vincent

AU - Renals, Steve

PY - 2002/5

Y1 - 2002/5

N2 - Support vector machines are evaluated on speaker verification and speaker identification tasks. We compare the polynomial kernel, the Fisher kernel, a likelihood ratio kernel and the pair hidden Markov model kernel with baseline systems based on a discriminative polynomial classifier and generative Gaussian mixture model classifiers. Simulations were carried out on the YOHO database and some promising results were obtained.

AB - Support vector machines are evaluated on speaker verification and speaker identification tasks. We compare the polynomial kernel, the Fisher kernel, a likelihood ratio kernel and the pair hidden Markov model kernel with baseline systems based on a discriminative polynomial classifier and generative Gaussian mixture model classifiers. Simulations were carried out on the YOHO database and some promising results were obtained.

U2 - 10.1109/ICASSP.2002.5743806

DO - 10.1109/ICASSP.2002.5743806

M3 - Conference contribution

SN - 0-7803-7402-9

SP - 669

EP - 672

BT - Proceedings of the 2002 IEEE International Conference on Acoustics, Speech, and Signal Processing

PB - Institute of Electrical and Electronics Engineers (IEEE)

T2 - 2002 IEEE International Conference on Acoustics, Speech, and Signal Processing

Y2 - 13 May 2002 through 17 May 2002

ER -

Evaluation of kernel methods for speaker verification and identification

Abstract / Description of output

Conference

Access to Document

Fingerprint

Cite this