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Development and Application of an AI Popular Science Digital Human System Based on Local Private Large Model Technology 认领 引用
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作者 Yongqiang Wang 《Journal of Electronic Research and Application》 2026年第5期187-193,共7页
With the continuous development of artificial intelligence technology,digital human technology offers extensive applications in science popularization education.This paper designs an AI popular science digital human s... With the continuous development of artificial intelligence technology,digital human technology offers extensive applications in science popularization education.This paper designs an AI popular science digital human system using local private large model technology,which integrates key technologies including speech recognition,natural language processing,speech synthesis,and digital human driving to enable intelligent interactive Q&A with users.The system adopts a locally deployed architecture,fine-tuned based on the Qwen large language model,and combines SenseVoice speech recognition,CosyVoice speech synthesis,and the LiveTalking digital human driving engine to build a complete popular science interaction process.The system has been put into practical use in scenarios such as science and technology festivals in primary and secondary schools and science and technology exhibition halls,which effectively improves the fun and interactivity of science popularization education and provides a new solution for cultivating scientific literacy among teenagers. 展开更多
关键词 Artificial intelligence Large language model Digital human Science popularization education Local deployment Intelligent interaction
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A Localized AIGC‑Live2D Workflow for Dynamic Virtual Human Clothing Generation:Deployment and Validation 认领 引用
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作者 Yang Yang 《Contemporary Design Studies》 2026年第2期114-128,共15页
Live2D creators on the open‑source digital human platforms face three core challenges:fragmented workflows,difficult local deployment,and low‑efficiency UV mapping.This study proposes a localized AIGC‑Live2D workflow ... Live2D creators on the open‑source digital human platforms face three core challenges:fragmented workflows,difficult local deployment,and low‑efficiency UV mapping.This study proposes a localized AIGC‑Live2D workflow with five sequential modules.The full workflow takes 31.2 minutes,improves efficiency by 75%over traditional manual UV mapping,and achieves 4.4/5 satisfaction among 30 professional designers.It solves texture misalignment and deployment barriers,lowers the creation threshold,and provides a replicable scheme for digital media art practitioners. 展开更多
关键词 Live2D AIGC virtual digital human Local Deployment UV mapping
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