Improving performance of speaker identification systems using score level fusion of two modes of operation

Saeid Safavi; Iosif Mporas

doi:10.1007/978-3-319-66429-3_43

Improving performance of speaker identification systems using score level fusion of two modes of operation

Saeid Safavi, Iosif Mporas

Centre for Engineering Research

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

4 Citations (Scopus)

Abstract

In this paper we present a score level fusion methodology for improving the performance of closed-set speaker identification. The fusion is performed on scores which are extracted from GMM-UBM text-dependent and text-independent speaker identification engines. The experimental results indicated that the score level fusion improves the speaker identification performance compared with the best performing single operation mode of speaker identification.

Original language	English
Title of host publication	Speech and Computer - 19th International Conference, SPECOM 2017, Proceedings
Editors	Alexey Karpov, Iosif Mporas, Rodmonga Potapova
Publisher	Springer Nature Link
Pages	438-444
Number of pages	7
ISBN (Print)	9783319664286
DOIs	https://doi.org/10.1007/978-3-319-66429-3_43
Publication status	Published - 1 Jan 2017
Event	19th International Conference on Speech and Computer, SPECOM 2017 - Hatfield, United Kingdom Duration: 12 Sept 2017 → 16 Sept 2017

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	10458 LNAI
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	19th International Conference on Speech and Computer, SPECOM 2017
Country/Territory	United Kingdom
City	Hatfield
Period	12/09/17 → 16/09/17

Keywords

Fusion
Learning
Machine
Speaker identification

Access to Document

10.1007/978-3-319-66429-3_43

Cite this

Safavi, S., & Mporas, I. (2017). Improving performance of speaker identification systems using score level fusion of two modes of operation. In A. Karpov, I. Mporas, & R. Potapova (Eds.), Speech and Computer - 19th International Conference, SPECOM 2017, Proceedings (pp. 438-444). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 10458 LNAI). Springer Nature Link. https://doi.org/10.1007/978-3-319-66429-3_43

Safavi, Saeid ; Mporas, Iosif. / Improving performance of speaker identification systems using score level fusion of two modes of operation. Speech and Computer - 19th International Conference, SPECOM 2017, Proceedings. editor / Alexey Karpov ; Iosif Mporas ; Rodmonga Potapova. Springer Nature Link, 2017. pp. 438-444 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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abstract = "In this paper we present a score level fusion methodology for improving the performance of closed-set speaker identification. The fusion is performed on scores which are extracted from GMM-UBM text-dependent and text-independent speaker identification engines. The experimental results indicated that the score level fusion improves the speaker identification performance compared with the best performing single operation mode of speaker identification.",

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Safavi, S & Mporas, I 2017, Improving performance of speaker identification systems using score level fusion of two modes of operation. in A Karpov, I Mporas & R Potapova (eds), Speech and Computer - 19th International Conference, SPECOM 2017, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 10458 LNAI, Springer Nature Link, pp. 438-444, 19th International Conference on Speech and Computer, SPECOM 2017, Hatfield, United Kingdom, 12/09/17. https://doi.org/10.1007/978-3-319-66429-3_43

Improving performance of speaker identification systems using score level fusion of two modes of operation. / Safavi, Saeid; Mporas, Iosif.
Speech and Computer - 19th International Conference, SPECOM 2017, Proceedings. ed. / Alexey Karpov; Iosif Mporas; Rodmonga Potapova. Springer Nature Link, 2017. p. 438-444 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 10458 LNAI).

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

TY - GEN

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AU - Safavi, Saeid

AU - Mporas, Iosif

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AB - In this paper we present a score level fusion methodology for improving the performance of closed-set speaker identification. The fusion is performed on scores which are extracted from GMM-UBM text-dependent and text-independent speaker identification engines. The experimental results indicated that the score level fusion improves the speaker identification performance compared with the best performing single operation mode of speaker identification.

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KW - Learning

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SN - 9783319664286

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

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BT - Speech and Computer - 19th International Conference, SPECOM 2017, Proceedings

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T2 - 19th International Conference on Speech and Computer, SPECOM 2017

Y2 - 12 September 2017 through 16 September 2017

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Safavi S, Mporas I. Improving performance of speaker identification systems using score level fusion of two modes of operation. In Karpov A, Mporas I, Potapova R, editors, Speech and Computer - 19th International Conference, SPECOM 2017, Proceedings. Springer Nature Link. 2017. p. 438-444. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-319-66429-3_43

Improving performance of speaker identification systems using score level fusion of two modes of operation

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Keywords

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