SmartKB: Morphologically Adaptive Virtual Keyboard in VR Based on Multimodal Character Prediction

SmartKB: Morphologically Adaptive Virtual Keyboard in VR Based on Multimodal Character Prediction | 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 SmartKB: Morphologically Adaptive Virtual Keyboard in VR Based on Multimodal Character Prediction Li Chen, Hengxin Chen, Haoran Li, Mingyi Wu This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7019957/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 In VR environment, the method of text-input by creating virtual surrogates for the keyboard and hands not only overcomes spatial constraints but also enhances users' sense of immersion. However, the input efficiency of virtual keyboards based on virtual surrogates is hindered by the accuracy of hand tracking. Especially in small vision-based tracking devices, hand occlusion leads to a decline in input efficiency. To enhance the input efficiency of virtual keyboards, we propose an optimization approach for virtual keyboards based on multimodal character prediction. This method integrates historical text and hand - motion trajectory information to build a multimodal character-prediction model. Based on this, a probability fusion strategy grounded in dynamic weights is designed. Probability serves as the driving force to update the key shapes, guiding users to input text efficiently. Compared with virtual keyboards in standard form, this method increases the text-input speed of virtual keyboards from 10.99 WPM to 14.08 WPM, and reduces the total error rate from 0.11 to 0.06. Virtual reality virtual keyboard character prediction 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-7019957","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":482415189,"identity":"55e49e85-e73a-4b7b-960c-9c918392d933","order_by":0,"name":"Li Chen","email":"","orcid":"","institution":"Chongqing University","correspondingAuthor":false,"prefix":"","firstName":"Li","middleName":"","lastName":"Chen","suffix":""},{"id":482415190,"identity":"79c30eac-a5c1-4cea-8fda-4ee544924c94","order_by":1,"name":"Hengxin Chen","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA8UlEQVRIiWNgGAWjYDACCQYGZjCDmYHxAUQogXgtzAYkamFgYJMgSgv/7OZjjwsq7thtOM57rOJH2WEGfvYcA4afO/BYcudYuvGMM8+SZzbzpd3sOXeYQbLnjQFj7xncWgwkcsykedsOJ/Mz85jdZmw7zGBwI8eAmbENn5b8b9K8/w4nswG1FIO02BPWksMmzdtw2A5kCzPYFgkCWiRupJlJ8xw7nCDZzGMs2XMunUfizLOCg714tPDPSH4mzVNz2N7g/BnDDz/KrOX425M3PviJRwsMJDaAKTYGHhB1gLAGBgZ7BqiWUTAKRsEoGAUYAADVmElDr8xlvwAAAABJRU5ErkJggg==","orcid":"","institution":"Chongqing University","correspondingAuthor":true,"prefix":"","firstName":"Hengxin","middleName":"","lastName":"Chen","suffix":""},{"id":482415191,"identity":"46522779-3427-4310-9360-9f1856fcc40d","order_by":2,"name":"Haoran Li","email":"","orcid":"","institution":"Chongqing University","correspondingAuthor":false,"prefix":"","firstName":"Haoran","middleName":"","lastName":"Li","suffix":""},{"id":482415192,"identity":"1e439a70-9408-4f6b-9826-c7c46b10d48e","order_by":3,"name":"Mingyi Wu","email":"","orcid":"","institution":"Chongqing University","correspondingAuthor":false,"prefix":"","firstName":"Mingyi","middleName":"","lastName":"Wu","suffix":""}],"badges":[],"createdAt":"2025-07-01 11:53:05","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7019957/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7019957/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":91596292,"identity":"bb9144fc-fcf1-4ed7-8ded-583ba494107d","added_by":"auto","created_at":"2025-09-18 07:39:15","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":3140022,"visible":true,"origin":"","legend":"","description":"","filename":"SmartKBMorphologicallyAdaptiveVirtualKeyboardinVRBasedonMultimodalCharacterPrediction.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7019957/v1_covered_be9992a4-d530-4223-a11a-aac952d10045.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"SmartKB: Morphologically Adaptive Virtual Keyboard in VR Based on Multimodal Character Prediction","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":"Virtual reality, virtual keyboard, character prediction","lastPublishedDoi":"10.21203/rs.3.rs-7019957/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7019957/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e In VR environment, the method of text-input by creating virtual surrogates for the keyboard and hands not only overcomes spatial constraints but also enhances users' sense of immersion. However, the input efficiency of virtual keyboards based on virtual surrogates is hindered by the accuracy of hand tracking. Especially in small vision-based tracking devices, hand occlusion leads to a decline in input efficiency. To enhance the input efficiency of virtual keyboards, we propose an optimization approach for virtual keyboards based on multimodal character prediction. This method integrates historical text and hand - motion trajectory information to build a multimodal character-prediction model. Based on this, a probability fusion strategy grounded in dynamic weights is designed. Probability serves as the driving force to update the key shapes, guiding users to input text efficiently. 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