Voice control in a real flight deck environment

Abstract

In this paper, we present a methodology on how to implement multimodal voice controlled systems by means of automatic speech recognition. The real flight deck environment brings many challenges such as high accuracy requirements, high noise conditions, non-native English-speaking users or limited hardware and software resources. We present the design of an automatic speech recognition system based on a freely available AMI Meeting Corpus and a proprietary corpus provided by Airbus. Then we describe how we trained and evaluated the speech recognition models in a simulated environment using the anechoic chamber laboratory. The tuned speech recognition models were tested in real flight environment on two Honeywell experimental airplanes: Dassault Falcon 900 and Boeing 757.