A study on the speaker recognition algorithm based on Bayesian compressed sensing theory

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dc.contributor.authorYan Yang
dc.contributor.authorLi Zhao
dc.date.accessioned2020-04-08T06:22:36Z
dc.date.available2020-04-08T06:22:36Z
dc.date.issued2019
dc.description.abstractSpeaker recognition technology is widely used in the Internet and communication filed. In recent years, compressed sensing theory attracted wide attention in and abroad. Having broken through the limitations of the Nyquist sampling rate, it can sampled compressible signals while compressing them at the same time.As a new theory, compressed sensing theory was brought into the filed of speaker recognition technology where huge breakthrough is in great demand to bring hope to enhance the performance of speaker recognition system. Aiming at the text independent speaker recognition technology, this paper made a profound study on the Bayesian compressed sensing algorithm. According to the characteristics of the sparse coefficient in the algorithm, a Gaussian prior assumption is introduced. And then a speaker recognition algorithm based on Bayesian compressed sensing is proposed.uk_UA
dc.identifier.citationYan Yang. A study on the speaker recognition algorithm based on Bayesian compressed sensing theory / Yan Yang, Li Zhao // Управління розвитком складних систем : зб. наук. праць / Київ. нац. ун-т буд-ва і архітектури ; гол. ред. Лізунов П. П. – Київ : КНУБА, 2019. – № 38. – С. 29-32. - Бібліогр. : 10 назв.uk_UA
dc.identifier.issn2219-5300
dc.identifier.urihttps://repositary.knuba.edu.ua/handle/987654321/2352
dc.language.isoenuk_UA
dc.publisherКНУБАuk_UA
dc.subjectspeakeruk_UA
dc.subjectrecognitionuk_UA
dc.subjectcompressed sensinguk_UA
dc.subjectsparse representationuk_UA
dc.subjectBCS GMMuk_UA
dc.subject.udc004.934.1'1uk_UA
dc.titleA study on the speaker recognition algorithm based on Bayesian compressed sensing theoryuk_UA
dc.typeArticleuk_UA

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