AI-Driven WebTV: An End-to-End Architecture for Automated Video Content Creation and Broadcasting

AI-Driven WebTV: An End-to-End Architecture for Automated Video Content Creation and Broadcasting | 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 AI-Driven WebTV: An End-to-End Architecture for Automated Video Content Creation and Broadcasting Haq Nawaz Malik, Syed Murtaza Rizvi This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5608661/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 This paper presents developing and implementing an AI-driven WebTV system designed to automate the video content creation pipeline, from conceptualization to broadcasting. Leveraging open-source models such as Zeroscope for text-to-video generation and MusicGen for music synthesis, the system integrates large language models (LLMs) to create a seamless, modular production architecture. The research explores the challenges of combining different AI components into a cohesive framework, highlighting issues such as real-time processing, video quality optimization, and model interoperability. The findings demonstrate the system’s ability to generate coherent, good-quality video and audio content autonomously, significantly reducing the need for human intervention in traditional video production workflows. Although the AI-driven WebTV system illustrates the potential for scalable, automated media production, limitations in scene complexity, frame interpolation, and content consistency are identified. Future work is suggested to enhance the system’s scalability, real-time adaptability, and ethical content generation. This research underscores the transformative potential of AI in media production, offering a foundation for future exploration into fully autonomous digital content creation. Artificial Intelligence and Machine Learning Computer Architecture and Engineering Theoretical Computer Science AI-Driven WebTV Text-to-Video Models Video Generation Automation Large Language Models Media Production Full Text Additional Declarations The authors declare no competing interests. The author confirmed that they would like this version processed and posted. 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. 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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-5608661","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":387994431,"identity":"26614794-89e6-4a66-bae3-b74a4cdd21f8","order_by":0,"name":"Haq Nawaz Malik","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA10lEQVRIiWNgGAWjYBACgwMwlgQziCkhQ4oWtgQQyUOKFh4DEEWElmuHn30uqDksLz+75/OrGzUWPAzsh49uwKvldprx7BnHDhs2zjm7zTrnGNBhPGlpN/BrSTBm5mG7zdgskbvNOIcNqEWCx4yAlvTPzDz/btu3SeQ8M875R5SWHGNm3rbbiT0SOcyPc9uI0CI5O6eYmbfvf/IMiTQz5tw+CR42Qn7hl07fzMzzLc12/ozkx59zvtXJ8bMfPoZXCzJgkwCTxCoHAeYPpKgeBaNgFIyCkQMAt0FGzxO8f2YAAAAASUVORK5CYII=","orcid":"https://orcid.org/0009-0003-1994-7640","institution":"Birla Institute of Technology And Science, Pilani (BITS Pilani)","correspondingAuthor":true,"prefix":"","firstName":"Haq","middleName":"Nawaz","lastName":"Malik","suffix":""},{"id":387994432,"identity":"04263168-8e79-41f8-b98f-09140d389ec0","order_by":1,"name":"Syed Murtaza Rizvi","email":"","orcid":"https://orcid.org/0009-0005-3738-4874","institution":"Birla Institute of Technology And Science, Pilani (BITS Pilani)","correspondingAuthor":false,"prefix":"","firstName":"Syed","middleName":"Murtaza","lastName":"Rizvi","suffix":""}],"badges":[],"createdAt":"2024-12-09 11:43:43","currentVersionCode":1,"declarations":{"humanSubjects":false,"vertebrateSubjects":false,"conflictsOfInterestStatement":false,"humanSubjectEthicalGuidelines":false,"humanSubjectConsent":false,"humanSubjectClinicalTrial":false,"humanSubjectCaseReport":false,"vertebrateSubjectEthicalGuidelines":false},"doi":"10.21203/rs.3.rs-5608661/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-5608661/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":78867017,"identity":"6b1a64d5-9364-461d-997b-5c13bf80b44c","added_by":"auto","created_at":"2025-03-20 04:23:57","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1337339,"visible":true,"origin":"","legend":"","description":"","filename":"BuildinganAIDrivenWebTVV1J8.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5608661/v1_covered_5d53f8f8-ef44-476e-9a1b-3c38405b30d5.pdf"}],"financialInterests":"\u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e\n\u003cp\u003eThe author confirmed that they would like this version processed and posted.\u003c/p\u003e","formattedTitle":"\u003cp\u003eAI-Driven WebTV: An End-to-End Architecture for Automated Video Content Creation and Broadcasting\u003c/p\u003e","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"Birla Institute of Technology and Science, Pilani","isAcceptedByJournal":false,"isAuthorSuppliedPdf":true,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":true,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"AI-Driven WebTV, Text-to-Video Models, Video Generation, Automation, Large Language Models, Media Production","lastPublishedDoi":"10.21203/rs.3.rs-5608661/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5608661/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThis paper presents developing and implementing an AI-driven WebTV system designed to automate the video content creation pipeline, from conceptualization to broadcasting. 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