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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

  • Czech description

Classification

  • Type

    D - Article in proceedings

  • CEP classification

  • 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

  • e-ISSN

  • 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