Please use this identifier to cite or link to this item: https://open.uns.ac.rs/handle/123456789/7401
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dc.contributor.authorPakoci, Edvinen
dc.contributor.authorJakovljević, Nikšaen
dc.contributor.authorPopović, Borisen
dc.contributor.authorMišković, Dragišaen
dc.contributor.authorPekar, Darkoen
dc.date.accessioned2019-09-30T09:01:43Z-
dc.date.available2019-09-30T09:01:43Z-
dc.date.issued2014-01-01en
dc.identifier.isbn9783319115801en
dc.identifier.issn3029743en
dc.identifier.urihttps://open.uns.ac.rs/handle/123456789/7401-
dc.description.abstract© Springer International Publishing Switzerland 2014. The paper presents a speaker detection system based on phoneme specific hidden Markov model in combination with Gaussian mixture model. Our motivation stems from the fact that the phoneme specific HMM system can model temporal variations and provides possibility to ponder the scores of specific phonemes as well as efficient pruning. The performance of the system has been evaluated on speech database which contains utterances in Serbian from 250 speakers (1 0 of them being the target speakers). The proposed model is compared to a system based on Gaussian mixture model - universal background model, and showed a significant improvement in detection performance.en
dc.relation.ispartofLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)en
dc.titleSpeaker detection using phoneme specific hidden markov modelsen
dc.typeConference Paperen
dc.identifier.scopus2-s2.0-84910072740en
dc.identifier.urlhttps://api.elsevier.com/content/abstract/scopus_id/84910072740en
dc.relation.lastpage417en
dc.relation.firstpage410en
dc.relation.volume8773en
item.fulltextNo Fulltext-
item.grantfulltextnone-
crisitem.author.deptFakultet tehničkih nauka, Departman za energetiku, elektroniku i telekomunikacije-
crisitem.author.parentorgFakultet tehničkih nauka-
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