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ATCO2

financed

Automatic collection and processing of voice data from air traffic communication...

Automatic collection and processing of voice data from air traffic communications ATCO2 will deliver a platform to collect, store, process and share voice communications from real world air-traffic control data, exploiting deep learning methods. The planned machine learning solutions are enabling technologies f... see more

28/02/2022

IDIAP

834K€

Project Budget: 834K€

Project leader

FONDATION DE LINSTITUT DE RECHERCHE IDIAP No se ha especificado una descripción o un objeto social para esta compañía.

TRL 4-5

PARTICIPATION DEPralty Sin fecha límite de participación.

Ver 7 Participantes

Financing granted El organismo H2020 notifico la concesión del proyecto The day 2022-02-28

JTI-CS2-2018-CFP09-LPA-03-16: Automated data collection and semi-... Specific Challenge:The aim is to develop infrastructure for automated collection of big data and imp...

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Este proyecto no cuenta con búsquedas de partenariado abiertas en este momento.

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7 Participantes

IDIAP

189.63K€ | Leader

ReplayWell SRO

41.74K€ | participant

USAAR

149.62K€ | participant

ROMAGNA TECH

50.75K€ | participant

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Project duration: 29 months Date Start: 2019-09-18
End date: 2022-02-28

Project leader

FONDATION DE LINSTITUT DE RECHERCHE IDIAP No se ha especificado una descripción o un objeto social para esta compañía.

TRL 4-5

Project Budget 834K€

participation deadline Sin fecha límite de participación.

Project description ATCO2 will deliver a platform to collect, store, process and share voice communications from real world air-traffic control data, exploiting deep learning methods. The planned machine learning solutions are enabling technologies for air-traffic control. To achieve robust and high speech recognition performance, large amount of data will be collected. The project aims at accessing data from certified ADS-B datalinks aligned with a surveillance technology, and directly from air-traffic controllers supplied by air navigation service providers. Centered on a robust platform, the project will build on an existing and extensively used solution of ‘OpenSky network’ partner, ensuring its long term sustainability. Current platform collects and stores periodically broadcasted aircraft information through a network of ADS-B receivers. It will be extended to allow collection, storage and pre-processing of voice communications, and time/position aligned with other aircraft information. The project targets both spoken commands issued by air-traffic controllers and readback confirmations provided by pilots. In addition to broadcasted data, ATCO2 will have access to voice recordings from air navigation service providers (e.g. Austrocontrol). Besides automatic segmentation (e.g. speaker, accent, specific command), robust automatic speech recognition will be implemented and integrated to automatically transcribe voice communications. It will use active learning scenarios capable of iterative improvements, in addition to manual post-editing. To comply with the CleanSky2 Programme, the project will also significantly contribute to community building, consolidating an existing community of ‘OpenSky network’. Project incentives will motivate users to upload and potentially pre-transcribe data to gain access to other resources and automatic transcripts. The project will strongly account for legal and ethical issues regarding privacy, personal data, data security and other related aspect

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