In the area of voice recognition, many methods have been proposed over time. Automatic speaker recognition technology has reached a good level of performance, but still needs to be improved. Signature verification (SV) is one of the most common methods of identity verification in the banking sector, where for security reasons, it is very important to have an accurate method for automatic signature verification (ASV). ASV is usually solved by comparing a test signature with a registration signature(-s) signed by the person whose identity is declared in two ways: online and offline. In this study, a new ivector based method is proposed for SV online. In the proposed method, a fixed-length vector, called an i-vector, is extracted from each signature, and then this vector is used to create a template. Several methods, such as the nuisance attribute projection and the within-class covariance normalization, are also being investigated to reduce the intra-class variation in the i-vector space. At the stage of evaluation and decision-making, they also propose to apply the support vector machine with two classes. In this article, a new low-dimensional space, depending on the dynamics and the channel, is determined using a simple factor analysis, also known as i-vector. I-vectors have proven to be the most efficient functions for text independent speaker verification in recent studies.

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NAS RK is pleased to announce that News of NAS RK. Series physico-mathematical journal has been accepted for indexing in the EmergingSources Citation Index, a new edition of Web of Science. Content in this index is under consideration by Clarivate Analytics to be accepted in the Science Citation Index Expanded, the Social Sciences Citation Index, and the Arts & Humanities Citation Index. The quality and depth of content Web of Science offers to researchers, authors, publishers, and institutions sets it apart from other research databases. The inclusion of News of NAS RK. Series of chemistry and technologies in the Emerging Sources Citation Index demonstrates our dedication to providing the most relevant and influential content of chemical sciences to our community. Қазақстан Республикасы Ұлттық ғылым академиясы «ҚР ҰҒА Хабарлары. Физикалық-математикалық сериясы» ғылыми журналының Web of Science-тің жаңаланған нұсқасы Emerging Sources Citation Index-me индекстелуге қабылданғанын хабарлайды. Бұл индекстелу барысында Clarivate Analytics компаниясы журналды одан әрі the Science Citation Index Expanded, the Social Sciences Citation Index және the Arts & Humanities Citation lndex-ке қабылдау мәселесін қарастыруда. Webof Science зерттеушілер, авторлар, баспашылар мен мекемелерге контент тереңдігі мен сапасын усынады. ҚР ҰҒА Хабарлары. Химия және технология сериясы Emerging Sources Citation lndex-ке енуі біздің қоғамдастық үшін ең өзекті және беделді химиялық ғылымдар бойынша контентке адалдығымызды білдіреді. HAH PK сообщает, что научный журнал «Известия HAH PK. Серия физико-математическая» был принят для индексирования в Emerging Sources Citation Index, обновленной версии Web of Science. Содержание в этом индексировании находится в стадии рассмотрения компанией Clarivate Analytics для дальнейшего принятия журнала в the Science Citation Index Expanded, the Social Sciences Citation Index и the Arts & Humanities Citation Index. Web of Science предлагает качество и глубину контента для исследователей, авторов, издателей и учреждений. Включение Известия HAH PK в Emerging Sources Citation Index демонстрирует нашу приверженность к наиболее актуальному и влиятельному контенту по химическим наукам для нашего сообщества.