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A New Method towards Speech Files Local Features Investigation

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dc.contributor.author Latypov R.
dc.contributor.author Stolov E.
dc.date.accessioned 2021-02-25T06:51:29Z
dc.date.available 2021-02-25T06:51:29Z
dc.date.issued 2020
dc.identifier.issn 1334-2630
dc.identifier.uri https://dspace.kpfu.ru/xmlui/handle/net/161124
dc.description.abstract © 2020 IEEE. There are a few reasons for the recent increased interest in studying the local features of speech files. It is stated that many of the essential properties of the speaker's language used may appear in the form of a speech signal. The traditional instruments-short Fourier transform, wavelet transform, Hadamard transforms, autocorrelation, and the like can detect not all peculiar properties of the language. In this paper, we propose a new approach to such characteristics exploration. The original signal is approximated by a new one, which values are taken from a finite set. We then construct a new sequence of fixed-size vectors based on these approximations. Studying the distribution of generated vectors provides a new way of describing the local attributes of speech files. Finally, the developed technique is applied to the problem of the automated distinguishing of two known languages used in speech files. For this, a simple neural net is constructed.
dc.relation.ispartofseries Proceedings Elmar - International Symposium Electronics in Marine
dc.subject Language distinguishing
dc.subject Local properties
dc.subject Neural net
dc.subject Speech files
dc.title A New Method towards Speech Files Local Features Investigation
dc.type Conference Paper
dc.relation.ispartofseries-volume 2020-September
dc.collection Публикации сотрудников КФУ
dc.relation.startpage 41
dc.source.id SCOPUS13342630-2020-2020-SID85093924853


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  • Публикации сотрудников КФУ Scopus [24551]
    Коллекция содержит публикации сотрудников Казанского федерального (до 2010 года Казанского государственного) университета, проиндексированные в БД Scopus, начиная с 1970г.

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