Leveraging Large Language Models to Expand Spoken Language Understanding Systems Across Multiple Languages

A pipeline leveraging Large Language Models (LLMs) for machine translation of slot-annotated spoken language understanding (SLU) training data can effectively extend SLU systems to new languages, outperforming existing state-of-the-art methods.