Project description
Speech-to-text solution in the air
Safety is the highest priority for the aviation industry. Continuous advances in technology make it easier to keep crews and passengers safe. One such development is automatic speech recognition technology that can reduce air-traffic controllers’ workload and minimise human error. However, voice recognition that turns speech to text remains limited due to difficulties in distinguishing controllers’ accents and deviations from standard terminology. The EU-funded HAAWAII project will study and develop a reliable, error-resilient and adaptable solution that automatically transcribes voice commands issues by both air-controllers and pilots. The project will use an extensive collection of data to develop a new set of models for complex environments of Icelandic en route and London TMA, focusing on strengthening speech recognition models.
Objective
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.
Fields of science (EuroSciVoc)
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: https://op.europa.eu/en/web/eu-vocabularies/euroscivoc.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: https://op.europa.eu/en/web/eu-vocabularies/euroscivoc.
- social sciences sociology industrial relations automation
- natural sciences computer and information sciences artificial intelligence machine learning
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Keywords
Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)
Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)
Programme(s)
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
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H2020-EU.3.4. - SOCIETAL CHALLENGES - Smart, Green And Integrated Transport
MAIN PROGRAMME
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H2020-EU.3.4.7. - SESAR JU
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Topic(s)
Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.
Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.
Funding Scheme
Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
RIA - Research and Innovation action
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Call for proposal
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
(opens in new window) H2020-SESAR-2019-2
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Net EU financial contribution. The sum of money that the participant receives, deducted by the EU contribution to its linked third party. It considers the distribution of the EU financial contribution between direct beneficiaries of the project and other types of participants, like third-party participants.
51147 KOLN
Germany
The total costs incurred by this organisation to participate in the project, including direct and indirect costs. This amount is a subset of the overall project budget.