Neural net as pseudo-inverse filter in speech coding problem

dc.contributor.author	Latypov R.
dc.contributor.author	Stolov E.
dc.date.accessioned	2020-01-15T22:12:01Z
dc.date.available	2020-01-15T22:12:01Z
dc.date.issued	2019
dc.identifier.uri	https://dspace.kpfu.ru/xmlui/handle/net/157007
dc.description.abstract	© 2019 IEEE. In the general case, a finite impulse response (FIR)filter has no inverse filter. To solve the inverse filtering problem, we propose an approximate method that restores the initial sequence. We analyze the sequence obtained by filtering the source sequence with an arbitrary FIR filter. The analysis made with the help of a deep neural network. The results of the study are applied to speech coding. We show experimentally, that our approach provides lowering bit rate in the transmission of speech data through a channel.
dc.subject	FR filter
dc.subject	neural net
dc.subject	pseudo-inverse filter
dc.subject	speech coding
dc.title	Neural net as pseudo-inverse filter in speech coding problem
dc.type	Conference Paper
dc.collection	Публикации сотрудников КФУ
dc.source.id	SCOPUS-2019-SID85075318580

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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.