A SEGMENTAL APPROACH TO TEXT-INDEPENDENT SPEAKER VERIFICATION

J. Černocký; D. Petrovska-Delacrétaz; S. Pigeon; Patrick Verlinde; G. Chollet

A SEGMENTAL APPROACH TO TEXT-INDEPENDENT SPEAKER VERIFICATION

J. Černocký, D. Petrovska-Delacrétaz, S. Pigeon, Patrick Verlinde, G. Chollet

Communication, Information, Systems and Sensors

Publikation: Beitrag in Buch/Bericht/Konferenzband › Konferenzbeitrag › Begutachtung

Abstract

Current text-independent speaker verification systems are usually based on modeling globally the probability density function (PDF) of the speaker feature vectors. In this paper, segmental approaches to text-independent speaker verification are discussed. Unlike the schemes based on Large Vocabulary Continuous Speech Recognition (LVCSR) with previously trained phone models, our systems are based on units derived in unsupervised manner using the ALISP (Automatic Language Independent Processing) tools. Speaker modeling is then done independently for each class of speech sounds. Among the techniques to merge the class-dependent scores, linear combination was tested and logistic regression and a method based on the Mixture of Experts technique are under investigation. The experimental results were obtained on the data from the NIST-NSA'98 campaign.

Originalsprache	Englisch
Titel	Proceedings of the 6th European Conference on Speech Communication and Technology, EUROSPEECH 1999
Seiten	2207-2210
Seitenumfang	4
Publikationsstatus	Veröffentlicht - 1999
Veranstaltung	6th European Conference on Speech Communication and Technology, EUROSPEECH 1999 - Budapest, Ungarn Dauer: 5 Sept. 1999 → 9 Sept. 1999

Konferenz

Konferenz	6th European Conference on Speech Communication and Technology, EUROSPEECH 1999
Land/Gebiet	Ungarn
Ort	Budapest
Zeitraum	5/09/99 → 9/09/99

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@inproceedings{230fed104f444b38b2e6c882e609a3ef,

title = "A SEGMENTAL APPROACH TO TEXT-INDEPENDENT SPEAKER VERIFICATION",

abstract = "Current text-independent speaker verification systems are usually based on modeling globally the probability density function (PDF) of the speaker feature vectors. In this paper, segmental approaches to text-independent speaker verification are discussed. Unlike the schemes based on Large Vocabulary Continuous Speech Recognition (LVCSR) with previously trained phone models, our systems are based on units derived in unsupervised manner using the ALISP (Automatic Language Independent Processing) tools. Speaker modeling is then done independently for each class of speech sounds. Among the techniques to merge the class-dependent scores, linear combination was tested and logistic regression and a method based on the Mixture of Experts technique are under investigation. The experimental results were obtained on the data from the NIST-NSA'98 campaign.",

keywords = "data fusion, segmental approach, text-independent speaker verification",

author = "J. {\v C}ernock{\'y} and D. Petrovska-Delacr{\'e}taz and S. Pigeon and Patrick Verlinde and G. Chollet",

note = "Publisher Copyright: {\textcopyright} 1999 6th European Conference on Speech Communication and Technology, EUROSPEECH 1999. All rights reserved.; 6th European Conference on Speech Communication and Technology, EUROSPEECH 1999 ; Conference date: 05-09-1999 Through 09-09-1999",

year = "1999",

language = "English",

pages = "2207--2210",

booktitle = "Proceedings of the 6th European Conference on Speech Communication and Technology, EUROSPEECH 1999",

}

Černocký, J, Petrovska-Delacrétaz, D, Pigeon, S, Verlinde, P & Chollet, G 1999, A SEGMENTAL APPROACH TO TEXT-INDEPENDENT SPEAKER VERIFICATION. in Proceedings of the 6th European Conference on Speech Communication and Technology, EUROSPEECH 1999. S. 2207-2210, 6th European Conference on Speech Communication and Technology, EUROSPEECH 1999, Budapest, Ungarn, 5/09/99.

TY - GEN

T1 - A SEGMENTAL APPROACH TO TEXT-INDEPENDENT SPEAKER VERIFICATION

AU - Černocký, J.

AU - Petrovska-Delacrétaz, D.

AU - Pigeon, S.

AU - Verlinde, Patrick

AU - Chollet, G.

PY - 1999

Y1 - 1999

N2 - Current text-independent speaker verification systems are usually based on modeling globally the probability density function (PDF) of the speaker feature vectors. In this paper, segmental approaches to text-independent speaker verification are discussed. Unlike the schemes based on Large Vocabulary Continuous Speech Recognition (LVCSR) with previously trained phone models, our systems are based on units derived in unsupervised manner using the ALISP (Automatic Language Independent Processing) tools. Speaker modeling is then done independently for each class of speech sounds. Among the techniques to merge the class-dependent scores, linear combination was tested and logistic regression and a method based on the Mixture of Experts technique are under investigation. The experimental results were obtained on the data from the NIST-NSA'98 campaign.

AB - Current text-independent speaker verification systems are usually based on modeling globally the probability density function (PDF) of the speaker feature vectors. In this paper, segmental approaches to text-independent speaker verification are discussed. Unlike the schemes based on Large Vocabulary Continuous Speech Recognition (LVCSR) with previously trained phone models, our systems are based on units derived in unsupervised manner using the ALISP (Automatic Language Independent Processing) tools. Speaker modeling is then done independently for each class of speech sounds. Among the techniques to merge the class-dependent scores, linear combination was tested and logistic regression and a method based on the Mixture of Experts technique are under investigation. The experimental results were obtained on the data from the NIST-NSA'98 campaign.

KW - data fusion

KW - segmental approach

KW - text-independent speaker verification

UR - http://www.scopus.com/inward/record.url?scp=34147191768&partnerID=8YFLogxK

M3 - Conference contribution

AN - SCOPUS:34147191768

SP - 2207

EP - 2210

BT - Proceedings of the 6th European Conference on Speech Communication and Technology, EUROSPEECH 1999

T2 - 6th European Conference on Speech Communication and Technology, EUROSPEECH 1999

Y2 - 5 September 1999 through 9 September 1999

ER -

A SEGMENTAL APPROACH TO TEXT-INDEPENDENT SPEAKER VERIFICATION

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