Descripción del proyecto
Una tecnología de voz a texto en el aire
La seguridad es la mayor prioridad del sector aeronáutico. Los continuos avances tecnológicos permiten mantener seguros a los pasajeros y la tripulación con más facilidad. Uno de estos avances es la tecnología de reconocimiento automático de voz, que puede reducir el volumen de trabajo de los controladores del tráfico aéreo y minimizar los errores humanos. Sin embargo, el reconocimiento de voz que convierte la voz en texto sigue siendo limitado debido a las dificultades para distinguir los acentos de los controladores y las variaciones de la terminología normalizada. El proyecto HAAWAII, financiado con fondos europeos, estudiará y desarrollará una tecnología fiable, adaptable y resistente a los errores que transcriba automáticamente los comandos de voz emitidos tanto por controladores aéreos como por los pilotos. El proyecto utilizará una colección exhaustiva de datos para desarrollar un nuevo conjunto de modelos para entornos complejos de navegación de Islandia y del área de control terminal londinense, centrándose en reforzar los modelos de reconocimiento de voz.
Objetivo
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.
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RIA - Research and Innovation actionCoordinador
51147 Koln
Alemania