ATC-Anno: Semantic Annotation for Air Traffic Control with Assistive Auto-Annotation

Publication
In Proceedings of the 12th Conference on Language Resources and Evaluation (LREC 2020)

Abstract

In air traffic control, assistant systems support air traffic controllers in their work. To improve the reactivity and accuracy of the assistant, automatic speech recognition can monitor the commands uttered by the controller. However, to provide sufficient training data for the speech recognition system, many hours of air traffic communications have to be transcribed and semantically annotated. For this purpose we develop the annotation tool ATC-ANNO. It provides a number of features to support the annotator in their task, such as auto-complete suggestions for semantic tags, access to preliminary speech recognition predictions, syntax highlighting and consistency indicators. Its core assistive feature, however, is its ability to automatically generate semantic annotations. Although it is based on a simple hand-written finite state grammar, it is also able to annotate sentences that deviate from this grammar. We evaluate the impact of different fea- tures on annotator efficiency and find that automatic annotation allows annotators to cover four times as many utterances in the same time.

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