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dc.contributor.authorGhahabi Esfahani, Omid
dc.contributor.authorHernando Pericás, Francisco Javier
dc.contributor.otherUniversitat Politècnica de Catalunya. Departament de Teoria del Senyal i Comunicacions
dc.date.accessioned2015-04-07T14:50:36Z
dc.date.created2014
dc.date.issued2014
dc.identifier.citationGhahabi, O.; Hernando, J. Deep belief networks for i-vector based speaker recognition. A: IEEE International Conference on Acoustics, Speech, and Signal Processing. "2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2014): Florence, Italy, 4-9 May 2014". Florència: Institute of Electrical and Electronics Engineers (IEEE), 2014, p. 1700-1704.
dc.identifier.isbn978-1-4799-2894-1
dc.identifier.urihttp://hdl.handle.net/2117/27145
dc.description.abstractThe use of Deep Belief Networks (DBNs) is proposed in this paper to model discriminatively target and impostor i-vectors in a speaker verification task. The authors propose to adapt the network parameters of each speaker from a background model, which will be referred to as Universal DBN (UDBN). It is also suggested to backpropagate class errors up to only one layer for few iterations before to train the network. Additionally, an impostor selection method is introduced which helps the DBN to outperform the cosine distance classifier. The evaluation is performed on the core test condition of the NIST SRE 2006 corpora, and it is shown that 10% and 8% relative improvements of EER and minDCF can be achieved, respectively.
dc.format.extent5 p.
dc.language.isoeng
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE)
dc.subjectÀrees temàtiques de la UPC::Enginyeria de la telecomunicació
dc.subjectÀrees temàtiques de la UPC::Informàtica
dc.subject.lcshNeural networks (Computer science)
dc.subject.otherDeep belief network
dc.subject.otheri-vector
dc.subject.otherNeural network
dc.subject.otherSpeaker recognition
dc.titleDeep belief networks for i-vector based speaker recognition
dc.typeConference report
dc.subject.lemacXarxes neuronals (Informàtica)
dc.contributor.groupUniversitat Politècnica de Catalunya. VEU - Grup de Tractament de la Parla
dc.identifier.doi10.1109/ICASSP.2014.6853888
dc.description.peerreviewedPeer Reviewed
dc.rights.accessRestricted access - publisher's policy
drac.iddocument15207525
dc.description.versionPostprint (published version)
dc.date.lift10000-01-01
upcommons.citation.authorGhahabi, O.; Hernando, J.
upcommons.citation.contributorIEEE International Conference on Acoustics, Speech, and Signal Processing
upcommons.citation.pubplaceFlorència
upcommons.citation.publishedtrue
upcommons.citation.publicationName2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2014): Florence, Italy, 4-9 May 2014
upcommons.citation.startingPage1700
upcommons.citation.endingPage1704
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