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Title: Method for Parametric Identification of Gaussian Mixture Model Based on Clonal Selection Algorithm
Authors: Fedorov, Eugene
Lukashenko, Valentyna
Utkina, Tetiana
Lukashenko, Andriy
Rudakov, Kostiantyn
Федоров, Євген Євгенович
Лукашенко, Валентина Максимівна
Уткіна, Тетяна Юріївна
Лукашенко, Андрій Германович
Рудаков, Костянтин Сергійович
Keywords: quasi-periodic signal;speaker recognition;gaussian mixture model;learning set formation;parametric identification;clonal selection algorithm
Issue Date: 2019
Publisher: CEUR Workshop Proceedings
Abstract: The problem of increasing the efficiency of parametric identification of Gaussian mixture model (GMM) is considered. A method for identifying GMM parameters based on clonal selection algorithm with preliminary formation of a learning set taking into account the structure of vocal sounds, which increases the likelihood of speaker recognition, is proposed. The parameter identification method is intended for software implementation on the GPU using the CUDA technology, which speeds up the process of parametric identification. This method has been studied on the TIMIT database and serves for intelligent systems of biometric personal identification.
ISSN: 1613-0073
Volume: 2353
First Page: 41
End Page: 55
Appears in Collections:Наукові публікації викладачів (ФІТІС)

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