IRWOZ 2.0 - A Large Language Model-driven Dialogue Dataset for Industrial Robot Conversations

IRWOZ has improved industrial human-robot interaction (HRI) dialogue systems through domain-specific annotations. However, its initial version contains substantial noise in dialogue states and utterances, limiting state-tracking accuracy. We introduce IRWOZ 2.0, which addresses these limitations through large language model (LLM) enhanced generation (Mistral\/Claude-3.5) and quality refinements. Our improveddataset expands to 390 dialogues across 4 industrial domains (Assembly, Delivery, Position, Relocation), featuring manual corrections and automated typo removal. Benchmark experiments on dialogue state tracking demonstrate significant improvements, with GPT-2\u2019s BLEU-4 score increasing from 0.1651 to 0.5604 compared to original IRWOZ.