Current Air Traffic Controllers(ATCO)training systems require human pseudo-pilot to complete the training procedure,which decreases the efficiency to controller simulation training.In this work,an automatic pilot agent(APA)framework is proposed to empower the controller simulation training systems.The proposed APA framework consists of four modules,including automatic speech recognition(ASR),controlling instruction understanding(CIU),controlling in-struction repetition(CIR),text-to-speech(TTS).Furthermore,a set of repeating rules are designed to adapt the various flight phase and ATC scenarios according to the ATC rules.In addition,the flight emergency handling module is integrat-ed in the proposed APA framework to improve the ability of the ATCO to handle the emergency situation intentionally and strategically.The experimental result shows that the proposed APA framework achieves desired performance,reaching 88.6％repetition accuracy,which can greatly improve controller training quality and efficiency,reduce human cost.In ad-dition,the proposed APA framework can integrate into the existing controller training simulator system as subsystem,which has strong convenience and compatibility.
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