Discriminatively Re-trained i-Vector Extractor For Speaker Recognition
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26230%2F19%3APU134183" target="_blank" >RIV/00216305:26230/19:PU134183 - isvavai.cz</a>
Result on the web
<a href="https://ieeexplore.ieee.org/document/8682590" target="_blank" >https://ieeexplore.ieee.org/document/8682590</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/ICASSP.2019.8682590" target="_blank" >10.1109/ICASSP.2019.8682590</a>
Alternative languages
Result language
angličtina
Original language name
Discriminatively Re-trained i-Vector Extractor For Speaker Recognition
Original language description
In this work we revisit discriminative training of the i-vector extractor component in the standard speaker verification (SV) system. The motivation of our research lies in the robustness and stability of this large generative model, which we want to preserve, and focus its power towards any intended SV task. We show that after generative initialization of the i-vector extractor, we can further refine it with discriminative training and obtain i-vectors that lead to better performance on various benchmarks representing different acoustic domains.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
Result was created during the realization of more than one project. More information in the Projects tab.
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2019
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Proceedings of ICASSP
ISBN
978-1-5386-4658-8
ISSN
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e-ISSN
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Number of pages
5
Pages from-to
6031-6035
Publisher name
IEEE Signal Processing Society
Place of publication
Brighton
Event location
Brighton
Event date
May 12, 2019
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
000482554006052