Urban search and rescue (USAR) teams may use Artificial Social Intelligence (ASI) agents to aid teams in adapting to dynamic environments, minimize risk, and increase mission assurance and task performance. This thesis underlines the relationship between vocal pitch, stress, and team performance from a recent experiment conducted in a simulated USAR synthetic task environment (STE). The simulated USAR-STE is a platform to use ASI as an advisor to intervene in the human team members’ cognitive processes, which aims to reduce risk to task execution and to maintain team performance. Three heterogeneous and interdependent roles interact via voice communication to search and rescue the victims: (1) medic -rescues victims and identifies the severity of injuries; (2) transporter -moves victims to their designated zone based on injury severity; (3) engineer -removes hazardous material such as rubble from a room or hallway that is blocking passage. Different speeds are associated with each role, such as medic, transporter, and engineer. Medic has a default speed; the transporter has times two over the default speed; the engineer has the slowest speed. In a total of 45 teams, three ASI conditions, manipulated based on ASI intervention communication length and frequency, were analyzed. Each team participated in two 15-min missions. The results indicate a U-shaped relationship between the transporter’s pitch and a change in team performance. A possible explanation for this significance is the task and role design. The transporter may have the most central role in voice communication because when the transporter is under varying levels of workload and stress, and thus voice pitch has a complex relationship with performance for that role.