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dc.contributor.advisorJahan,Sifat E
dc.contributor.advisorRasel, Annajiat Alim
dc.contributor.authorRhythm, Ehsanur Rahman
dc.contributor.authorArnob, Shafakat Sowroar
dc.contributor.authorShuvo, Rajvir Ahmed
dc.date.accessioned2024-06-25T03:29:58Z
dc.date.available2024-06-25T03:29:58Z
dc.date.copyright©2023
dc.date.issued2023-09
dc.identifier.otherID 22241163
dc.identifier.otherID 20101129
dc.identifier.otherID 20141003
dc.identifier.urihttp://hdl.handle.net/10361/23554
dc.descriptionThis thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2023.en_US
dc.descriptionCataloged from PDF version of thesis.
dc.descriptionIncludes bibliographical references (pages 51-53).
dc.description.abstractFor audio or video material to be more inclusive and accessible, automatic subtitle generation is essential. Nevertheless, implementing this technology into Bengali presents significant challenges due to scarce resources and linguistic difficulty. In this study, a new deep learning based system for creating Subtitles for Bengali multimedia automatically is introduced. The suggested approach makes use of the Wav2vec2 and the Common Voice Bengali Dataset, a large collection of Bengali audio recordings. This study uses the Common Voice Dataset Bengali to train and tune the Wav2vec2 model in order to accurately convert Bengali audio into text. Current automatic speech recognition approaches are combined with Bengali language-specific factors in the created system to give accurate and reliable transcription works. The transcribed text is synced with the matching audio parts throughout the subtitle production process. The produced subtitles are enhanced using post-processing approaches, similar to capitalization and punctuation restoration, to ensure readability and consistency. The findings of this study might greatly improve Bengali language media’s usability and availability across a range of sectors. The created subtitles may enhance the watching experience for Bengali multimedia by easing greater understanding, and expanding availability. The study demonstrates the potential of using deep learning and ASR methods to get over the difficulties of automated subtitle production in the Bengali language, advancing multimedia availability and inclusion.en_US
dc.description.statementofresponsibilityEhsanur Rahman Rhythm
dc.description.statementofresponsibilityShafakat Sowroar Arnob
dc.description.statementofresponsibilityRajvir Ahmed Shuvo
dc.format.extent62 pages
dc.language.isoenen_US
dc.publisherBrac Universityen_US
dc.rightsBrac University theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission.
dc.subjectAutomatic subtitle generationen_US
dc.subjectBengali audioen_US
dc.subjectDeep learningen_US
dc.subjectNatural language processingen_US
dc.subject.lcshNatural language processing (Computer science)
dc.subject.lcshComputational linguistics
dc.subject.lcshData mining
dc.titleAutomatic subtitle generation for Bengali multimedia using deep learningen_US
dc.typeThesisen_US
dc.contributor.departmentDepartment of Computer Science and Engineering, Brac University
dc.description.degreeB.Sc in Computer Science


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