Laurens Meeus
2024
AI4Culture: Towards Multilingual Access for Cultural Heritage Data
Tom Vanallemeersch
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Sara Szoc
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Laurens Meeus
Proceedings of the 25th Annual Conference of the European Association for Machine Translation (Volume 2)
The AI4Culture project (2023-2025), funded by the European Commission, and involving a 12-partner consortium led by the National Technical University of Athens, develops a platform serving as an online capacity building hub for AI technologies in the cultural heritage (CH) sector, enabling multilingual access to CH data. It offers access to AI-related resources, including openly labelled datasets for model training and testing, deployable and reusable tools, and capacity building materials. The tools are aimed at optical character recognition (OCR) for printed and handwritten documents, subtitle generation and validation, machine translation (MT), and metadata enrichment via image information extraction and semantic linking. The project also customises these tools to enhance interface and component usability. We illustrate this with technology that corrects OCR output using language models and adapts it for MT.
2022
Automatically extracting the semantic network out of public services to support cities becoming Smart Cities
Joachim Van den Bogaert
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Laurens Meeus
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Alina Kramchaninova
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Arne Defauw
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Sara Szoc
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Frederic Everaert
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Koen Van Winckel
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Anna Bardadym
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Tom Vanallemeersch
Proceedings of the 23rd Annual Conference of the European Association for Machine Translation
The CEFAT4Cities project aims at creating a multilingual semantic interoperability layer for Smart Cities that allows users from all EU member States to interact with public services in their own language. The CEFAT4Cities processing pipeline transforms natural-language administrative procedures into machine-readable data using various multilingual Natural Language Processing techniques, such as semantic networks and machine translation, thus allowing for the development of more sophisticated and more user-friendly public services applications.
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Co-authors
- Tom Vanallemeersch 2
- Sara Szoc 2
- Joachim Van Den Bogaert 1
- Alina Kramchaninova 1
- Arne Defauw 1
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