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Sign language detection and conversion to readable Bengali words using BdSL

bracu.degree.levelUndergraduate
bracu.type.groupStudent Works
datacite.rightsOpen Access
dc.contributor.advisorHossain, Muhammad Iqbal
dc.contributor.authorDhrubo, Tahsinul Haque
dc.contributor.authorMahmood, ASM Tareq
dc.contributor.authorTabassum, Noshin
dc.contributor.authorKhan, Riead Hasan
dc.contributor.departmentDepartment of Computer Science and Engineering
dc.date.accessioned2024-06-25T06:13:09Z
dc.date.available2024-06-25T06:13:09Z
dc.date.copyright2023
dc.date.issued2023-09
dc.descriptionCataloged from the PDF version of the thesis.
dc.descriptionIncludes bibliographical references (pages 32-33).
dc.descriptionThis thesis is submitted in partial fulfillment of the requirements for the degree of Master of Science in Computer Science, 2023.en_US
dc.description.abstractIn this era of modernization, technology is used to improve the outcome in every aspect of our lives. At the beginning of development, scientists made tools and pieces of stuff in order to enhance the speed of communication. The purpose of our research is to use modern technology to upgrade the lifestyle of human beings with the people who are struggling with obstacles. The machine interpretation of sign language has been conceivable yet in a restricted design, starting around 1977. At the point when an examination project effectively paired English letters from a console to ASL manual set letters which were reenacted on a mechanical hand. These innovations make an interpretation of sign language into a communicative language to communicate via gestures. The point of what is being looked for is now coming up. It’s already started to develop tools in order to make the communication procedure easier for people who can communicate with others through sign language. The objective of our endeavor is to provide a means of communication that facilitates interaction between those who possess normal hearing abilities and those who are deaf. The proposed system aims to identify indicators of deafness in individuals and use natural language processing (NLP) techniques to turn these indicators into a language that is readily understood, hence facilitating seamless communication between individuals with and without hearing impairments. The BDSL was used to enrich the dataset. In the event that an individual desires to use the model for a different language, it becomes required to make an update of the dataset. Our motto is - “Communications for everyone”.en_US
dc.description.degreeBachelor of Science in Computer Science
dc.description.statementofresponsibilityTahsinul Haque Dhrubo
dc.description.statementofresponsibilityASM Tareq Mahmood
dc.description.statementofresponsibilityNoshin Tabassum
dc.description.statementofresponsibilityRiead Hasan Khan
dc.format.extent33 pages
dc.identifier.otherID 22341077
dc.identifier.otherID 20101073
dc.identifier.otherID 20101347
dc.identifier.otherID 20101004
dc.identifier.urihttp://hdl.handle.net/10361/23574
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.subjectDeaf peopleen_US
dc.subjectCamera visionen_US
dc.subjectReal-time communicationen_US
dc.subjectSign languageen_US
dc.subjectMediapipeen_US
dc.subject.lcshNatural language processing (Computer science).
dc.titleSign language detection and conversion to readable Bengali words using BdSLen_US
dc.typeThesisen_US

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