Show simple item record

dc.contributor.authorPakyurek, M.
dc.contributor.authorAtmış, Mahir
dc.contributor.authorKulac, S.
dc.contributor.authorUludag, U.
dc.date.accessioned2021-06-28T09:05:47Z
dc.date.available2021-06-28T09:05:47Z
dc.date.issued2020-02-17
dc.identifier.issn1392-1215en_US
dc.identifier.urihttp://hdl.handle.net/10679/7449
dc.identifier.urihttps://eejournal.ktu.lt/index.php/elt/article/view/25309
dc.description.abstractThis paper introduces two significant contributions: one is a new feature based on histograms of MFCC (Mel-Frequency Cepstral Coefficients) extracted from the audio files that can be used in emotion classification from speech signals, and the other – our new multi-lingual and multi-personal speech database, which has three emotions. In this study, Berlin Database (BD) (in German) and our custom PAU database (in English) created from YouTube videos and popular TV shows are employed to train and evaluate the test results. Experimental results show that our proposed features lead to better classification of results than the current state-of-the-art approaches with Support Vector Machine (SVM) from the literature. Thanks to our novel feature, this study can outperform a number of MFCC features and SVM classifier based studies, including recent researches. Due to the lack of our novel feature based approaches, one of the most common MFCC and SVM framework is implemented and one of the most common database Berlin DB is used to compare our novel approach with these kind of approaches.en_US
dc.language.isoengen_US
dc.publisherKauno Technologijos Universitetasen_US
dc.relation.ispartofElektronika ir Elektrotechnika
dc.rightsopenAccess
dc.titleExtraction of novel features based on histograms of mfccs used in emotion classification from generated original speech dataseten_US
dc.typeArticleen_US
dc.description.versionPublisher versionen_US
dc.peerreviewedyesen_US
dc.publicationstatusPublisheden_US
dc.contributor.departmentÖzyeğin University
dc.identifier.volume26en_US
dc.identifier.issue1en_US
dc.identifier.startpage46en_US
dc.identifier.endpage51en_US
dc.identifier.doi10.5755/j01.eie.26.1.25310en_US
dc.subject.keywordsEmotion classificationen_US
dc.subject.keywordsMFCCen_US
dc.subject.keywordsSpeech signalen_US
dc.subject.keywordsSVMen_US
dc.identifier.scopusSCOPUS:2-s2.0-85082514166
dc.contributor.ozugradstudentAtmış, Mahir
dc.contributor.authorMale1
dc.relation.publicationcategoryArticle - International Refereed Journal - Institutional PhD Student


Files in this item

Thumbnail

This item appears in the following Collection(s)

Show simple item record


Share this page