Integrated Memory Control and Thread Scheduling for Real-Time Voice Interaction Systems

Integrated Memory Control and Thread Scheduling for Real-Time Voice Interaction Systems | 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 Integrated Memory Control and Thread Scheduling for Real-Time Voice Interaction Systems Michael R. Hughes, Yanling Zhou, Daniel K. Morgan This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7863332/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 Intelligent voice assistants need to keep response delay low and service stable while running on devices with limited hardware resources. This study used a dual-path method that joins fine memory control with multi-thread asynchronous scheduling. A total of 118 runs were carried out on smartphones, embedded boards, and wearables under both controlled and office settings. The results showed that median response time fell by 27% and 99th-percentile delay fell by 34%. System throughput rose by 22%, and stability improved by about 30%. Accuracy stayed steady, with word error rate changes within 0.2 and F1 score changes within 0.3. Processing cost was reduced by about 42% compared with standard models. These outcomes show that delay and stability can be improved together without loss in accuracy. The method can support faster and steadier voice assistants, though more devices, longer tests, and far-field or multi-language data should be included in future work. Electrical Engineering intelligent voice assistant low delay system stability memory control asynchronous scheduling edge devices Full Text Additional Declarations The authors declare no competing interests. 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-7863332","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":529775188,"identity":"8221caed-a278-40c0-828a-f8cd59ed1324","order_by":0,"name":"Michael R. 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