SBIR/STTR Award attributes
In this proposed effort, the team of Mosaic ATM and Aptima leverage their individual proven track records, as well as previous collaboration, to create the Reconfigurable Interactive Communication Training Environment (RICTE) using a combination of two primary technical approaches – domain simulation modeling and deep-learning-based dialogue agents. The goal of the RICTE is to easily generate and evaluate text/chat and verbal communication in a training environment applied to the Air Traffic Control (ATC) domain, that can also be adapted to other domains. The proposed training system will utilize AI and ML technology to provide an intelligent, realistic, and autonomous communications software tool that provides relevant voice and text/chat information exchanges. The system will have the ability to provide synthesized speech in response to student voice communications, significantly improving scenario realism while simultaneously reducing instructor workload. The fidelity of this tool will be a significant improvement over current systems concerning realism, tailorability, instructor workload, and student learning. The system will be modular, scalable, flexible, and platform agnostic with potential for future expansion into a stand-alone capability within the classified arena.
