Automatic Understanding of ATC Speech

In this paper we make a critical revision of the state-of-the-art in automatic speech processing as applied to Air Traffic Control. We present the development of a new ATC speech understanding system comparing its performance and advantages to previously published experiences. The system has innovative solutions such as detecting the Air/Ground language spoken by Air Traffic Controllers in an international airport with two official languages and the ability to adapt to new situations by automatically learning stochastic grammars from data, eliminating the need to write expensive and eternally incomplete grammars. A relevant new feature is the use of a speech understanding module able to extract semantically relevant information from the transcription of the sentences delivered by the speech recognizers. Two main assessment objectives are pursued and discussed throughout the paper: the effects of human spontaneity and the lack of linguistic coverage in understanding performance. The potential of this technology, ways of improvement, and proposals for the future are also presented.