Comparison of the effectiveness of machine learning classifiers in the context of voice biometrics

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Datum:2019
Hauptverfasser: Ya. Danylov, Ya. V. Hrushko
Format: Artikel
Sprache:Englisch
Veröffentlicht: 2019
Schriftenreihe:System researches & information technologies
Online Zugang:http://jnas.nbuv.gov.ua/article/UJRN-0001075418
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Назва журналу:Library portal of National Academy of Sciences of Ukraine | LibNAS

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Library portal of National Academy of Sciences of Ukraine | LibNAS
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author Ya. Danylov
Ya. V. Hrushko
author_facet Ya. Danylov
Ya. V. Hrushko
author_sort Ya. Danylov
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institution Library portal of National Academy of Sciences of Ukraine | LibNAS
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spelling open-sciencenbuvgovua-228842024-02-26T22:25:02Z Comparison of the effectiveness of machine learning classifiers in the context of voice biometrics Ya. Danylov Ya. V. Hrushko 1681-6048 2019 en System researches & information technologies http://jnas.nbuv.gov.ua/article/UJRN-0001075418 Article
spellingShingle System researches & information technologies
Ya. Danylov
Ya. V. Hrushko
Comparison of the effectiveness of machine learning classifiers in the context of voice biometrics
title Comparison of the effectiveness of machine learning classifiers in the context of voice biometrics
title_full Comparison of the effectiveness of machine learning classifiers in the context of voice biometrics
title_fullStr Comparison of the effectiveness of machine learning classifiers in the context of voice biometrics
title_full_unstemmed Comparison of the effectiveness of machine learning classifiers in the context of voice biometrics
title_short Comparison of the effectiveness of machine learning classifiers in the context of voice biometrics
title_sort comparison of the effectiveness of machine learning classifiers in the context of voice biometrics
url http://jnas.nbuv.gov.ua/article/UJRN-0001075418
work_keys_str_mv AT yadanylov comparisonoftheeffectivenessofmachinelearningclassifiersinthecontextofvoicebiometrics
AT yavhrushko comparisonoftheeffectivenessofmachinelearningclassifiersinthecontextofvoicebiometrics