打造高保真实时对话数字人，支持自然互动与情感表达。
Hi-Reco: High-Fidelity Real-Time Conversational Digital Humans
- 异步流水线协调多模态组件，降低延迟实现实时响应。
- 引入历史增强与意图路由，提升对话连贯性与知识获取效率。
- 适合沉浸式通信、教育、娱乐场景，表现逼真且交互流畅。
高保真数字人日益应用于交互场景，但兼顾视觉真实感与实时响应仍是难题。本文提出一个高保真、实时对话数字人系统，无缝融合视觉逼真的3D形象、基于人格特征的语音合成以及基于知识的对话生成。为实现自然及时的交互，设计了异步执行流水线，最小化多模态组件间的延迟。系统支持唤醒词检测、情感化语调表达及高度准确、上下文感知的回应生成。通过新颖的检索增强方法，包括历史增强以维持对话连贯性，以及基于意图的路由实现高效知识访问。这些组件共同构成一个集成系统，使数字人具备强响应能力与可信表现，适用于通信、教育和娱乐等沉浸式应用。
原文摘要 · Abstract (English)
High-fidelity digital humans are increasingly used in interactive applications, yet achieving both visual realism and real-time responsiveness remains a major challenge. We present a high-fidelity, real-time conversational digital human system that seamlessly combines a visually realistic 3D avatar, persona-driven expressive speech synthesis, and knowledge-grounded dialogue generation. To support natural and timely interaction, we introduce an asynchronous execution pipeline that coordinates multi-modal components with minimal latency. The system supports advanced features such as wake word detection, emotionally expressive prosody, and highly accurate, context-aware response generation. It leverages novel retrieval-augmented methods, including history augmentation to maintain conversational flow and intent-based routing for efficient knowledge access. Together, these components form an integrated system that enables responsive and believable digital humans, suitable for immersive applications in communication, education, and entertainment.
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