Autonomous Drone Racing (ADR) has garnered significant interest in the aerial robotics commu- nity. Early solutions used classical computer vi- sion algorithms for gate detection, while more recent approaches employed visual Simultane- ous Localisation and Mapping (SLAM). The lat- est advancements have showcased solutions ca- pable of winning races against world champi- ons. However, these rely primarily on visual data from onboard cameras, whereas humans com- plement visual sensing with auditory perception. Motivated by the benefits of auditory perception, this study investigates the use of audio signal processing to detect when a drone crosses a gate during a race. This detection addresses the blind spot issue, where the gate disappears from the visual sensor’s view after crossing. Initial results indicate the feasibility of using audio signals to identify gate crossings, based on sound changes caused by drone propellers. This is a first effort to explore the broader potential of auditory per- ception in autonomous drone racing.