I Was Blind but Now I See: Implementing Vision-Enabled Dialogue in Social Robots

• URL: http://arxiv.org/abs/2311.08957v1
• Date: Wed, 15 Nov 2023 13:47:00 GMT
• Title: I Was Blind but Now I See: Implementing Vision-Enabled Dialogue in Social Robots
• Authors: Giulio Antonio Abbo and Tony Belpaeme
• Abstract summary: This paper presents an initial implementation of a dialogue manager that enhances the traditional text-based prompts with real-time visual input. The system's prompt engineering, incorporating dialogue with summarisation of the images, ensures a balance between context preservation and computational efficiency.
• Score: 0.040792653193642496
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: In the rapidly evolving landscape of human-computer interaction, the integration of vision capabilities into conversational agents stands as a crucial advancement. This paper presents an initial implementation of a dialogue manager that leverages the latest progress in Large Language Models (e.g., GPT-4, IDEFICS) to enhance the traditional text-based prompts with real-time visual input. LLMs are used to interpret both textual prompts and visual stimuli, creating a more contextually aware conversational agent. The system's prompt engineering, incorporating dialogue with summarisation of the images, ensures a balance between context preservation and computational efficiency. Six interactions with a Furhat robot powered by this system are reported, illustrating and discussing the results obtained. By implementing this vision-enabled dialogue system, the paper envisions a future where conversational agents seamlessly blend textual and visual modalities, enabling richer, more context-aware dialogues.

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