Natural Language Processing for Joint Fire Observer Training

摘要

We describe recent research to enhance a training system which interprets Call for Fire (CFF) radio artillery requests. The research explores the feasibility of extending the system to also understand calls for Close Air Support (CAS). This work includes automated analysis of complex language behavior in CAS missions, evaluation of speech recognition performance, and simulation of speech recognition errors.