Effect of speech bandwidth on speaker recognition performance using deep neural network (DNN).

dc.contributor.author	HADJERSI, Youcef
dc.contributor.author	HAMMOU, Oussama
dc.contributor.author	KROBBA, Ahmed
dc.date.accessioned	2022-05-18T14:14:45Z
dc.date.available	2022-05-18T14:14:45Z
dc.date.issued	2020
dc.description.abstract	This work studies the general problem posed by the speaker recognition system in mobile environments with an effect of interest the bandwidth and speech coding. This is a comparative study on the performance of the speaker recognition system under different AMR Multi-Rate voice codecs and the bandwidths (NB narrowband, WB wideband and BEW wideband extension) based on the DNN approach.	fr
dc.identifier.citation	systemes des Telecommunications	fr
dc.identifier.govdoc	M120301
dc.identifier.uri	https://dspace.univ-medea.dz/handle/123456789/2781
dc.language.iso	fr	fr
dc.relation.ispartofseries	MF 4713;
dc.subject	Speaker recognition	fr
dc.subject	Deep Neural Network	fr
dc.subject	NB	fr
dc.subject	WB	fr
dc.subject	BWE	fr
dc.title	Effect of speech bandwidth on speaker recognition performance using deep neural network (DNN).	fr
dc.type	Memoire	fr

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