Speech Segmentation Using Bayesian Autoregressive Changepoint Detector

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dc.contributor.authorCmejla, R.
dc.contributor.authorSovka, Pavel
dc.coverage.issue4cs
dc.coverage.volume7cs
dc.date.accessioned2016-05-05T10:58:38Z
dc.date.available2016-05-05T10:58:38Z
dc.date.issued1998-12cs
dc.description.abstractThis submission is devoted to the study of the Bayesian autoregressive changepoint detector (BCD) and its use for speech segmentation. Results of the detector application to autoregressive signals as well as to real speech are given. BCD basic properties are described and discussed. The novel two-step algorithm consisting of cepstral analysis and BCD for automatic speech segmentation is suggested.en
dc.formattextcs
dc.format.extent14-17cs
dc.format.mimetypeapplication/pdfen
dc.identifier.citationRadioengineering. 1998, vol. 7, č. 4, s. 14-17. ISSN 1210-2512cs
dc.identifier.issn1210-2512
dc.identifier.urihttp://hdl.handle.net/11012/58344
dc.language.isoencs
dc.publisherSpolečnost pro radioelektronické inženýrstvícs
dc.relation.ispartofRadioengineeringcs
dc.relation.urihttp://www.radioeng.cz/fulltexts/1998/98_04_03.pdfcs
dc.rightsCreative Commons Attribution 3.0 Unported Licenseen
dc.rights.accessopenAccessen
dc.rights.urihttp://creativecommons.org/licenses/by/3.0/en
dc.subjectspeech segmentationen
dc.subjectsub-word boundariesen
dc.subjectcepstral analysisen
dc.subjectBayesian methodsen
dc.subjectchangepoint detectoren
dc.subjectautocorrelationen
dc.titleSpeech Segmentation Using Bayesian Autoregressive Changepoint Detectoren
dc.type.driverarticleen
dc.type.statusPeer-revieweden
dc.type.versionpublishedVersionen
eprints.affiliatedInstitution.facultyFakulta eletrotechniky a komunikačních technologiícs
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