Advancing Inclusion through Speech Technology with a Bibliometric Study of AI-based Sign Language Recognition

Advancing Inclusion through Speech Technology with a Bibliometric Study of AI-based Sign Language Recognition | 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 Systematic Review Advancing Inclusion through Speech Technology with a Bibliometric Study of AI-based Sign Language Recognition Rajsee Joshi Shah This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7173168/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 Objective : This paper explores the evolution and scope of research at the intersection of artificial intelligence and assistive speech technologies, with a specific focus on hearing, speech, and language disabilities. It examines how Sign Language Recognition (SLR) systems have advanced as a crucial tool for bridging communication gaps between the hearing-impaired community and the broader auditory society. Data Description : Employing a bibliometric analysis of 3,039 journal articles and conference proceedings indexed in the Scopus database between 1980 and 2024, this study maps the intellectual and technological development of AI-powered SLR. VOSviewer was used for analytical visualization, highlighting publication trajectories, growth phases, geographic research distribution, key contributing nations, author collaboration networks, and keyword co-occurrences. Results : The results indicate that scholarly interest in SLR began around 1985, with a marked acceleration in output since 2016. India and China have emerged as significant contributors to the field. The analysis of keywords and co-citations reveals shifting technological paradigms—from early reliance on Hidden Markov Models and Kinect sensors to more recent applications of deep learning, transfer learning, LSTM networks, attention mechanisms, and transformer architectures. This study contributes to the field of speech technology by offering a comprehensive overview of how AI-driven SLR research is shaping inclusive communication for individuals with speech and hearing impairments. Speech Technology Bibliometric analysis Sign-language recognition Artificial intelligence 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. 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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-7173168","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Systematic Review","associatedPublications":[],"authors":[{"id":502898596,"identity":"bc40b02c-4f4c-444c-bf09-25e0ba892388","order_by":0,"name":"Rajsee Joshi Shah","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA7klEQVRIie3QsUoDMRzH8V8J3BTbNeVEX+EvB5aCD5NQ6FSl4H6ty00+gIelfQVdbg4EdDn3/+DSxclBOXBRxNzg4pC70SHfMeGTP/kDsdi/zEKAoKGE/T3oTRLdl8ATtERSPzK5cq5ZLvOL0e31h3ovcDRkPWhkgBzah3l6Q+5SPT9V47JANmYt0hBRqE+FJGvWfF6lBxXMHWt0kayRlJsdL15asvJEfHYQSiUJ//giaYkm1knHFP8XSc7c8zyblt/qpKz3xXQTIspvTH7lZsuzPb/VZ8fDx5nj1wCBsn+mAoN1CACjjvtYLBaL4QcZ809Ac8rILQAAAABJRU5ErkJggg==","orcid":"","institution":"University of Wollongong","correspondingAuthor":true,"prefix":"","firstName":"Rajsee","middleName":"Joshi","lastName":"Shah","suffix":""}],"badges":[],"createdAt":"2025-07-21 04:38:10","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7173168/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7173168/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":95197139,"identity":"923bd4b6-08a3-4820-b41c-d221d65a543b","added_by":"auto","created_at":"2025-11-05 11:38:44","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1268834,"visible":true,"origin":"","legend":"","description":"","filename":"AdvancingInclusionthroughSpeechTechnologywithaBibliometricStudyofAIbasedSignLanguageRecognition.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7173168/v1_covered_f3ca5568-390f-4caa-ac4b-d62af489e0b7.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"\u003cp\u003eAdvancing Inclusion through Speech Technology with a Bibliometric Study of AI-based Sign Language Recognition\u003c/p\u003e","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","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":"Speech Technology, Bibliometric analysis, Sign-language recognition, Artificial intelligence","lastPublishedDoi":"10.21203/rs.3.rs-7173168/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7173168/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eObjective\u003c/strong\u003e: This paper explores the evolution and scope of research at the intersection of artificial intelligence and assistive speech technologies, with a specific focus on hearing, speech, and language disabilities. It examines how Sign Language Recognition (SLR) systems have advanced as a crucial tool for bridging communication gaps between the hearing-impaired community and the broader auditory society.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Description\u003c/strong\u003e: Employing a bibliometric analysis of 3,039 journal articles and conference proceedings indexed in the Scopus database between 1980 and 2024, this study maps the intellectual and technological development of AI-powered SLR. VOSviewer was used for analytical visualization, highlighting publication trajectories, growth phases, geographic research distribution, key contributing nations, author collaboration networks, and keyword co-occurrences.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults\u003c/strong\u003e: The results indicate that scholarly interest in SLR began around 1985, with a marked acceleration in output since 2016. 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