Conversational AI without the Cloud: A Lightweight, Local Dialogue Pipeline for Non-commercial Social Robots

A major limitation of current social robots is their dependence on cloud-based dialogue pipelines, which restricts use in settings with limited or unreliable connectivity. We present a lightweight, fully local spoken-dialogue system that runs on consumer-grade hardware and integrates open-source models for speech recognition , dialogue generation, and text-to-speech. The pipeline was deployed on Euclid, a non-commercial humanoid robot, across several public engagement events, enabling extended real-world interaction without internet access. We analyse over 5,000 dialogue turns recorded during these dialogues to characterise system behaviour , user interaction patterns, and challenges arising in noisy, multi-speaker environments. Our observations demonstrate the feasibility of privacy-preserving, on-device conversational robotics while highlighting limitations in turn-taking, response length, and environmental grounding. We outline planned improvements to support more robust and accessible social-robot interaction.