Automated Speech Recognition for Air Traffic Control

Nowadays, instructions from air traffic control (ATC) to pilots are usually given via voice communication, but controllers need to manually type all the information into the electronic flight strip systems. Recent years has seen significant progress made with machine learning applications that improve the performance of automatic speech recognition (ASR), making it possible to convert spoken words into digital machine-readable formats with the reliability required in the safety critical ATC domain.

This new technology offers the means to avoid the manual input of given ATC commands and enables safety improvements like automatic read-back error detection support and automatic call sign detection.

Within SESAR 2020, several projects are researching and developing ASR technologies to see what they can bring to the ATC working environment. This webinar aims to give the state-of-play of SESAR JU research and development, and in particular:

• Provide an overview of why voice recognition has taken so long to arrive to ATC;
• Showcase some of the more advanced ASR applications being researched under the SESAR 2020 Exploratory Research programme.
• Give the audience a chance to hear experiences of ANSPs working on the applications within the SESAR programme;

Agenda:

Welcome and Introduction
Olivia Nunez, ATM Expert, SESAR Joint Undertaking

The need for research on ASR in ATM
Hon. Prof. Dr. Hartmut Helmke, HAAWAII project lead, DLR

Illuminating flights using speech recognition
Raquel Garcia Lasheras, R&D Engineer, CRIDA

Application of ASR in the tower environment
Ramona Santarelli, Engineer, ENAV

The view of an Air Navigation Service Provider: The costs and benefits of ASR for Austro Control
Christian Kern, Director of Operations, Austro Control
Christian Windisch, Senior Air Traffic Management Expert, Austro Control

Questions and Answers
Moderated by Olivia Nunez, ATM Expert, SESAR Joint Undertaking