Extraction and comparison of various prosodic feature sets on sentence segmentation task for Turkish broadcast news data

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dc.authorid0000-0002-7035-8724
dc.authorid0000-0002-4597-0954
dc.authorid0000-0002-7008-4778
dc.contributor.authorDalva, Doğanen_US
dc.contributor.authorRevidi, İzel D.en_US
dc.contributor.authorGüz, Ümiten_US
dc.contributor.authorGürkan, Hakanen_US
dc.date.accessioned2015-11-24T14:01:04Z
dc.date.available2015-11-24T14:01:04Z
dc.date.issued2014
dc.departmentIşık Üniversitesi, Mühendislik Fakültesi, Elektrik-Elektronik Mühendisliği Bölümüen_US
dc.departmentIşık University, Faculty of Engineering, Department of Electrical-Electronics Engineeringen_US
dc.description.abstractIn this work, prosodic features of the Turkish Broadcast News (BN) data are extracted using an open source prosodic feature extraction tool based on Praat. The profiles and effectiveness of these features are also investigated for the sentence segmentation task on the Turkish BN data. We not only used some combinations of the feature sets but also collected some of them in one prosodic feature model in order to achieve one of the best performance. The results of the experiments show that some combinations of the prosodic feature sets are very useful for the automatic sentence segmentation task on the Turkish BN data.en_US
dc.description.versionPublisher's Versionen_US
dc.identifier.citationDalva, D., Revidi, İ. D., Güz, Ü. & Gürkan, H. (2014). Extraction and comparison of various prosodic feature sets on sentence segmentation task for turkish broadcast news data. Paper presented at the 2014 11th International Joint Conference on Computer Science and Software Engineering (JCSSE), 70-73. doi:10.1109/JCSSE.2014.6841844en_US
dc.identifier.doi10.1109/JCSSE.2014.6841844
dc.identifier.endpage73
dc.identifier.isbn9781479958221
dc.identifier.isbn9781479958214
dc.identifier.issn2372-1642
dc.identifier.scopus2-s2.0-84904569487
dc.identifier.scopusqualityN/A
dc.identifier.startpage70
dc.identifier.urihttps://hdl.handle.net/11729/718
dc.identifier.urihttp://dx.doi.org/10.1109/JCSSE.2014.6841844
dc.identifier.wosWOS:000359800000013
dc.identifier.wosqualityN/A
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.indekslendigikaynakConference Proceedings Citation Index – Science (CPCI-S)en_US
dc.institutionauthorDalva, Doğanen_US
dc.institutionauthorRevidi, İzel D.en_US
dc.institutionauthorGüz, Ümiten_US
dc.institutionauthorGürkan, Hakanen_US
dc.institutionauthorid0000-0002-7035-8724
dc.institutionauthorid0000-0002-4597-0954
dc.institutionauthorid0000-0002-7008-4778
dc.language.isoenen_US
dc.peerreviewedYesen_US
dc.publicationstatusPublisheden_US
dc.publisherIEEEen_US
dc.relation.ispartof2014 11th International Joint Conference on Computer Science and Software Engineering (JCSSE)en_US
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectProsodic Feature Extractionen_US
dc.subjectProsodyen_US
dc.subjectSentence Segmentationen_US
dc.subjectPraaten_US
dc.subjectTurkish Broadcast News dataen_US
dc.subjectOpen source prosodic feature extraction toolen_US
dc.subjectProsodic feature setsen_US
dc.subjectSentence segmentation tasken_US
dc.subjectFeature extraction
dc.subjectNatural language processingen_US
dc.subjectPublic domain softwareen_US
dc.subjectTask analysisen_US
dc.titleExtraction and comparison of various prosodic feature sets on sentence segmentation task for Turkish broadcast news dataen_US
dc.typeConference Objecten_US
dspace.entity.typePublication

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