Automatic Speech Recognition for Air Traffic Control Using Open Data

Abstract

Air Traffic Control (ATC) is tasked with ensuring safe separation between aircraft in a given Controlled Traffic Region (CTR). To achieve this an Air Traffic Controller (ATCo) verbally gives clearances using over the air communication. These clearances are kept track of by the ATCo using so-called ‘flight-strips’, which in modern systems are often digital. The allocation of an ATCo’s time is an important factor in the achievable traffic density within a CTA, which makes ATC an interesting domain to use Automatic Speech Recognition (ASR) models to allow a computer system to ‘listen in’ to the conversation of the ATCo. Although previous research has been done to create such models, few of these result in open available models or domain specific corpora for the creation of such a model. This study will therefore use two open in-domain and one out-of-domain corpora to create such a model and in this process identify domain specific challenges and how these challenges can, in certain cases, be mitigated.