Role-playing LLMs in professional communication training : the case of investigative interviews with children

We present a novel approach for professional communication training in which Large Language Models (LLMs) are guided to dynamically adapt to inappropriate communication techniques by producing false information that match the biased expectations of an interviewer. We achieve this by dynamically altering the LLM’s system prompt in conjunction with a classifier that detects undesirable communication behaviour. We develop this approach for training German speaking criminal investigators who interview children in alleged sexual abuse cases. We describe how our approach operationalises the strict communication requirements for such interviews and how it is integrated into a full, end-to-end learning environment that supports speech interaction with 3D virtual characters. We evaluate several aspects of this environment and report the positive results of an initial user study.