A Multilingual Intelligent System for Objectionable Text Recognition Utilizing an Explainable AI-Supported Deep Learning Model on Bengali, Bengali Transliteration, and English Embedded Text

A Multilingual Intelligent System for Objectionable Text Recognition Utilizing an Explainable AI-Supported Deep Learning Model on Bengali, Bengali Transliteration, and English Embedded Text | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article A Multilingual Intelligent System for Objectionable Text Recognition Utilizing an Explainable AI-Supported Deep Learning Model on Bengali, Bengali Transliteration, and English Embedded Text Mohammad Sayem Chowdhury, Tofayet Sultan, Nusrat Jahan, Md. Asraf Ali, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4193833/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract We live in a global society that has benefited greatly from the rise of social media, which has become a potent agent of social change. However, toxic use of text or images may damage online communities and even spark intergroup confrontations. A precise approach is needed to deal with harmful or offensive information that specifically targets people or groups. Existing literature has generally focused on a particular language of hate speech detection using typical machine learning algorithms, where a few applied deep learning, resulting in a comparatively better outcome. However, not enough work has been dedicated to Bengali or transliterating Bengali text. This means the creation of a multilingual intelligent system that is able to recognize slang and abusive language from text or photographs is the current challenge that has to be addressed for Bengali users. Based on the crisis and deep technical comparison, our research proposed the robust multilingual expert system using mBERT as a baseline model with updates utilizing global average pooling and dense dropout. Here, we received an accuracy of 92%, higher than any of the competing methods. Then, the inclusion of OCR also evaporated the issue from the image. Additionally, we utilized LIME explainable AI to demonstrate the transparency of our model. Hate speech detection Deep learning Natural language processing Cyberbullying Explainable AI Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4193833","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":285809647,"identity":"bcef5546-f8ed-4f54-a106-160bd4038e43","order_by":0,"name":"Mohammad Sayem Chowdhury","email":"","orcid":"","institution":"American International University-Bangladesh","correspondingAuthor":false,"prefix":"","firstName":"Mohammad","middleName":"Sayem","lastName":"Chowdhury","suffix":""},{"id":285809650,"identity":"f23e4037-a354-4c1c-8ca8-58d24af7520f","order_by":1,"name":"Tofayet Sultan","email":"","orcid":"","institution":"American International University-Bangladesh","correspondingAuthor":false,"prefix":"","firstName":"Tofayet","middleName":"","lastName":"Sultan","suffix":""},{"id":285809652,"identity":"ef11e98e-282f-4ba3-a430-a6931818af63","order_by":2,"name":"Nusrat Jahan","email":"","orcid":"","institution":"American International University-Bangladesh","correspondingAuthor":false,"prefix":"","firstName":"Nusrat","middleName":"","lastName":"Jahan","suffix":""},{"id":285809654,"identity":"f24b6725-6d5c-4ce4-9d32-e3f8de65d5b4","order_by":3,"name":"Md. 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