Improving the Understanding between Control Tower Operator and Pilot Using Semantic Techniques — A New Approach

For aviation safety human related mistakes cannot be neglected. Control tower operators can become a potential risk for aviation safety. These operators check the status of aircraft by visualization and their communication with the pilot starts when the aircraft is near the runway. Due to the environment in which these operators work these operators can have problems hearing the pilot. To minimize the risk of misunderstanding between operator and pilot higher accuracy of communication is required. A solution that can record the voice of both controller and pilot and semantically categorize it can be useful for the controller to ensure aviation safety. In this paper we have proposed such a system. The proposed training-less text categorization engine of the system uses knowledgebase approach for retrieving the semantics required. System architecture has been described covering speech recognition, Natural Language Processing and Word Sense Disambiguation.