AIVA: An AI-based Virtual Companion for Emotion-aware Interaction
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arXiv
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| Format: | Preprint |
| Published: |
2025
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| _version_ | 1866916930950004736 |
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| author | Li, Chenxi |
| author_facet | Li, Chenxi |
| contents | Recent advances in Large Language Models (LLMs) have significantly improved natural language understanding and generation, enhancing Human-Computer Interaction (HCI). However, LLMs are limited to unimodal text processing and lack the ability to interpret emotional cues from non-verbal signals, hindering more immersive and empathetic interactions. This work explores integrating multimodal sentiment perception into LLMs to create emotion-aware agents. We propose \ours, an AI-based virtual companion that captures multimodal sentiment cues, enabling emotionally aligned and animated HCI. \ours introduces a Multimodal Sentiment Perception Network (MSPN) using a cross-modal fusion transformer and supervised contrastive learning to provide emotional cues. Additionally, we develop an emotion-aware prompt engineering strategy for generating empathetic responses and integrate a Text-to-Speech (TTS) system and animated avatar module for expressive interactions. \ours provides a framework for emotion-aware agents with applications in companion robotics, social care, mental health, and human-centered AI. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2509_03212 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | AIVA: An AI-based Virtual Companion for Emotion-aware Interaction Li, Chenxi Computer Vision and Pattern Recognition Recent advances in Large Language Models (LLMs) have significantly improved natural language understanding and generation, enhancing Human-Computer Interaction (HCI). However, LLMs are limited to unimodal text processing and lack the ability to interpret emotional cues from non-verbal signals, hindering more immersive and empathetic interactions. This work explores integrating multimodal sentiment perception into LLMs to create emotion-aware agents. We propose \ours, an AI-based virtual companion that captures multimodal sentiment cues, enabling emotionally aligned and animated HCI. \ours introduces a Multimodal Sentiment Perception Network (MSPN) using a cross-modal fusion transformer and supervised contrastive learning to provide emotional cues. Additionally, we develop an emotion-aware prompt engineering strategy for generating empathetic responses and integrate a Text-to-Speech (TTS) system and animated avatar module for expressive interactions. \ours provides a framework for emotion-aware agents with applications in companion robotics, social care, mental health, and human-centered AI. |
| title | AIVA: An AI-based Virtual Companion for Emotion-aware Interaction |
| topic | Computer Vision and Pattern Recognition |
| url | https://arxiv.org/abs/2509.03212 |