Livia是一款能感知情绪的AR伴侣,会随时间自适应进化。
Livia: An Emotion-Aware AR Companion Powered by Modular AI Agents and Progressive Memory Compression
- 用模块化AI分工处理情绪、对话、记忆和行为
- 新算法压缩记忆存储,省下70%空间仍保留关键信息
- 适合需要情感陪伴或想体验拟人化AR交互的人
孤独与社交隔离带来重大情绪与健康挑战,推动了技术型陪伴解决方案的发展。本文提出Livia,一款基于模块化AI代理与渐进式记忆压缩的情绪感知增强现实(AR)伴侣应用,通过多模态情感计算和具身交互实现个性化情感支持。Livia采用模块化架构,由专门负责情绪分析、对话生成、记忆管理和行为编排的AI代理协同工作,确保互动的鲁棒性与适应性。提出两种新算法——时间二值压缩(TBC)与动态重要性记忆过滤(DIMF),有效管理长期记忆,显著降低存储需求同时保留关键上下文。多模态情绪检测方法达到高准确率,提升主动共情能力。用户评估显示,情感联结增强,满意度提高,孤独感显著下降。用户尤其认可其自适应人格演化与逼真的AR具身表现。未来研究方向包括拓展手势与触觉交互、支持多人体验,以及定制硬件实现。
原文摘要 · Abstract (English)
Loneliness and social isolation pose significant emotional and health challenges, prompting the development of technology-based solutions for companionship and emotional support. This paper introduces Livia, an emotion-aware augmented reality (AR) companion app designed to provide personalized emotional support by combining modular artificial intelligence (AI) agents, multimodal affective computing, progressive memory compression, and AR driven embodied interaction. Livia employs a modular AI architecture with specialized agents responsible for emotion analysis, dialogue generation, memory management, and behavioral orchestration, ensuring robust and adaptive interactions. Two novel algorithms-Temporal Binary Compression (TBC) and Dynamic Importance Memory Filter (DIMF)-effectively manage and prioritize long-term memory, significantly reducing storage requirements while retaining critical context. Our multimodal emotion detection approach achieves high accuracy, enhancing proactive and empathetic engagement. User evaluations demonstrated increased emotional bonds, improved satisfaction, and statistically significant reductions in loneliness. Users particularly valued Livia's adaptive personality evolution and realistic AR embodiment. Future research directions include expanding gesture and tactile interactions, supporting multi-user experiences, and exploring customized hardware implementations.
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