arXiv 2603.030602026-03-03eess.IVeess.AS

DLIOS：一种增强现实时间多模态交互增强叠加系统的大型语言模型增强系统，用于抖音直播

DLIOS: An LLM-Augmented Real-Time Multi-Modal Interactive Enhancement Overlay System for Douyin Live Streaming

University of Toronto（多伦多大学）；Hohai University（河海大学）；University of Bristol（布里斯托大学）；Harbin Institute of Technology（哈尔滨工业大学）

Shuide Wen, Sungil Seok, Beier Ku, Richee Li, Yubin He, Bowen Qu, Yang Yang, Ping Su, Can Jiao

备注：: 14 pages, 13 figures, 6 tables, 7 algorithms, 16 references, submitted to ACM/IEEE International Conference on Systems and Software Engineering

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AI总结：

DLIOS通过LLM增强实时多模态交互增强系统，实现抖音直播中的弹幕、礼物效果和TTS广播的高效处理与优化。

摘要：

我们介绍了DLIOS，一种为抖音（TikTok）直播增强的大型语言模型（LLM）增强的实时多模态交互增强叠加系统。DLIOS采用三层透明窗口架构，用于独立渲染弹幕（滚动文本）、礼物和点赞粒子效果以及VIP入口动画，基于事件驱动的WebView2捕获管道和线程安全的事件总线。在此基础上，我们贡献了一个LLM广播自动化框架，包括：（1）每首歌曲四段提示调度系统（T1开场/过渡，T2共情，T3时代故事/制作说明，T4结尾），从歌词元数据生成情感连贯的广播式评论；（2）支持热切换多角色广播的JSON可序列化RadioPersonaConfig架构；（3）实时弹幕快速反应引擎，通过关键词路由到静态紧急语音或LLM生成的共情响应；（4）Suwan Li AI歌手作曲人案例研究——使用Suno生成超过100首AI歌曲。36小时压力测试显示：零弹幕重叠，零死锁崩溃，礼物效果P95延迟<=180 ms，LLM到TTS段P95延迟<=2.1秒，TTS集成响度增益为9.5 LUFS。

英文摘要：

We present DLIOS, a Large Language Model (LLM)-augmented real-time multi-modal interactive enhancement overlay system for Douyin (TikTok) live streaming. DLIOS employs a three-layer transparent window architecture for independent rendering of danmaku (scrolling text), gift and like particle effects, and VIP entrance animations, built around an event-driven WebView2 capture pipeline and a thread-safe event bus. On top of this foundation we contribute an LLM broadcast automation framework comprising: (1) a per-song four-segment prompt scheduling system (T1 opening/transition, T2 empathy, T3 era story/production notes, T4 closing) that generates emotionally coherent radio-style commentary from lyric metadata; (2) a JSON-serializable RadioPersonaConfig schema supporting hot-swap multi-persona broadcasting; (3) a real-time danmaku quick-reaction engine with keyword routing to static urgent speech or LLM-generated empathetic responses; and (4) the Suwan Li AI singer-songwriter persona case study -- over 100 AI-generated songs produced with Suno. A 36-hour stress test demonstrates: zero danmaku overlap, zero deadlock crashes, gift effect P95 latency <= 180 ms, LLM-to-TTS segment P95 latency <= 2.1 s, and TTS integrated loudness gain of 9.5 LUFS. live streaming; danmaku; large language model; prompt engineering; virtual persona; WebView2; WINMM; TTS; Suno; loudness normalization; real-time scheduling

机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。