Description du projet
Une solution de synthèse vocale pour le trafic aérien
La sécurité est la priorité absolue du secteur aéronautique. Des progrès technologiques continus ont permis d’assurer plus facilement la sécurité des équipages et des passagers. L’une de ces évolutions concerne la technologie de reconnaissance vocale automatique, capable de réduire la charge de travail des contrôleurs aériens et de minimiser les risques d’erreur humaine. Toutefois, la reconnaissance vocale (transformation des paroles en texte) reste limitée en raison des difficultés à distinguer les accents des contrôleurs et certains écarts par rapport à la terminologie standard. Le projet HAAWAII, financé par l’UE, étudiera et développera une solution fiable, résistante aux erreurs et adaptable qui transcrira automatiquement les commandes vocales des contrôleurs aériens et des pilotes. Le projet s’appuiera sur un vaste ensemble de données collectées pour élaborer un nouveau jeu de modèles destiné aux environnements complexes des routes aériennes d’Islande et des zones de manœuvre terminale (TMA) de Londres, en se concentrant sur le renforcement des modèles de reconnaissance vocale.
Objectif
Advanced automation support developed in Wave 1 of SESAR IR includes using of automatic speech recognition (ASR) to reduce the amount of manual data inputs by air-traffic controllers. Evaluation of controllers’ feedback has been subdued due to the limited recognition performance of the commercial of the shell ASR engines that were used, even in laboratory conditions. The reasons for the unsatisfactory conclusions include e.g. inability to distinguish controllers’ accents, deviations from standard phraseology and limited real-time recognition performance. Past exploratory research funded project MALORCA, however, has shown (on restricted use-cases) that satisfactory performance can be reached with novel data-driven machine learning approaches.
Based on the results of MALORCA HAAWAII project aims to research and develop a reliable, error resilient and adaptable solution to automatically transcribe voice commands issued by both air-traffic controllers and pilots. The project will build on very large collection of data, organized with a minimum expert effort to develop a new set of models for complex environments of Icelandic en-route and London TMA. HAAWAII aims to perform proof-of-concept trials in challenging environments, i.e. to be directly connected with real-life data from ops room. As pilot read-back error detection is the main application, HAAWAII aims to significantly enhance the validity of the speech recognition models. The proposed work goes far beyond the work planned for the Wave 2 IR programme and will improve both safety and reduce controllers’ workload. The digitization of controller and pilot voice utterances can be used for a wide variety of safety and performance related benefits including, but not limiting to pre-fill entries into electronic flight strips and CPDLC messages. Another application demonstrated during proof-of-concept will be to objectively estimate controllers’ workload utilising digitized voice recordings of the complex London TMA.
Champ scientifique
Mots‑clés
Programme(s)
Régime de financement
RIA - Research and Innovation actionCoordinateur
51147 Koln
Allemagne