QT21 | QT21: Quality Translation 21

Summary
A European Digital Single Market free of barriers, including language barriers, is a stated EU objective to be achieved by 2020. The findings of the META-NET Language White Papers show that currently only 3 of the EU-27 languages enjoy moderate to good support by our machine translation technologies, with either weak (at best fragmentary) or no support for the vast majority of the EU-27 languages. This lack is a key obstacle impeding the free flow of people, information and trade in the European Digital Single Market. Many of the languages not supported by our current technologies show common traits: they are morphologically complex, with free and diverse word order. Often there are not enough training resources and/or processing tools. Together this results in drastic drops in translation quality. The combined challenges of linguistic phenomena and resource scenarios have created a large and under-explored grey area in the language technology map of European languages. Combining support from key stakeholders, QT21 addresses this grey area developing (1) substantially improved statistical and machine-learning based translation models for challenging languages and resource scenarios, (2) improved evaluation and continuous learning from mistakes, guided by a systematic analysis of quality barriers, informed by human translators, (3) all with a strong focus on scalability, to ensure that learning and decoding with these models is efficient and that reliance on data (annotated or not) is minimised. To continuously measure progress, and to provide a platform for sharing and collaboration (QT21 internally and beyond), the project revolves around a series of Shared Tasks, for maximum impact co-organised with WMT. To support early technology transfer, QT21 proposes a Technology Bridge linking ICT-17(a) and (b) projects and opening up the possibility of showing technical feasibility of early research outputs in near to operational environments.
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More information & hyperlinks
Web resources: https://cordis.europa.eu/project/id/645452
Start date: 01-02-2015
End date: 31-01-2018
Total budget - Public funding: 3 997 428,00 Euro - 3 977 428,00 Euro
Cordis data

Original description

A European Digital Single Market free of barriers, including language barriers, is a stated EU objective to be achieved by 2020. The findings of the META-NET Language White Papers show that currently only 3 of the EU-27 languages enjoy moderate to good support by our machine translation technologies, with either weak (at best fragmentary) or no support for the vast majority of the EU-27 languages. This lack is a key obstacle impeding the free flow of people, information and trade in the European Digital Single Market. Many of the languages not supported by our current technologies show common traits: they are morphologically complex, with free and diverse word order. Often there are not enough training resources and/or processing tools. Together this results in drastic drops in translation quality. The combined challenges of linguistic phenomena and resource scenarios have created a large and under-explored grey area in the language technology map of European languages. Combining support from key stakeholders, QT21 addresses this grey area developing (1) substantially improved statistical and machine-learning based translation models for challenging languages and resource scenarios, (2) improved evaluation and continuous learning from mistakes, guided by a systematic analysis of quality barriers, informed by human translators, (3) all with a strong focus on scalability, to ensure that learning and decoding with these models is efficient and that reliance on data (annotated or not) is minimised. To continuously measure progress, and to provide a platform for sharing and collaboration (QT21 internally and beyond), the project revolves around a series of Shared Tasks, for maximum impact co-organised with WMT. To support early technology transfer, QT21 proposes a Technology Bridge linking ICT-17(a) and (b) projects and opening up the possibility of showing technical feasibility of early research outputs in near to operational environments.

Status

CLOSED

Call topic

ICT-17-2014

Update Date

27-10-2022
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Horizon 2020
H2020-EU.2. INDUSTRIAL LEADERSHIP
H2020-EU.2.1. INDUSTRIAL LEADERSHIP - Leadership in enabling and industrial technologies
H2020-EU.2.1.1. INDUSTRIAL LEADERSHIP - Leadership in enabling and industrial technologies - Information and Communication Technologies (ICT)
H2020-EU.2.1.1.4. Content technologies and information management: ICT for digital content, cultural and creative industries
H2020-ICT-2014-1
ICT-17-2014 Cracking the language barrier