Abstract
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.
Abstract (translated)
孤独和社会隔离带来了重大的情感和健康挑战，促使开发基于技术的解决方案来提供陪伴和支持。本文介绍了一款名为Livia的应用程序，它是一款结合模块化人工智能（AI）代理、多模态情感计算、渐进式记忆压缩以及增强现实（AR）驱动的具身互动的情感感知AR伴侣应用，旨在为用户提供个性化的心理支持。 Livia采用了一个模块化的人工智能架构，其中各个专门负责情绪分析、对话生成、记忆管理和行为编排的代理确保了强大而适应性的交互。该应用程序还采用了两种新颖算法——时间二进制压缩（TBC）和动态重要性记忆过滤器（DIMF），这些算法能够有效地管理和优先处理长期记忆，大大减少了存储需求的同时保留了关键上下文信息。 我们的多模态情绪检测方法实现了高精度，并增强了主动性和共情式的互动。用户评估表明，Livia的应用显著增加了情感联系、提高了满意度以及统计上明显地减轻了孤独感。特别是，用户特别赞赏Livia的适应性个性演变和真实的AR呈现方式。 未来的研究方向包括扩展手势与触觉交互的支持、支持多用户体验以及探索定制化硬件实现。
URL
https://arxiv.org/abs/2509.05298
