AI4Culture

Partners

CrossLang

National Technical University of Athens (laboratory Intelligent Systems, Content and Interaction)

Europeana Foundation (Netherlands)

Datoptron (Greece)

FBK (Fondazione Bruno Kessler, Machine Translation Research Unit, Italy)

Translated (Italy)

Datable (Belgium)

Pangeanic (Spain)

University of Leuven (DigitGLAM unit)

European Fashion Heritage Association (Italy)

Institute for Sound and Vision (Netherlands)

Austrian Institute of Technology

Project Description

The consortium of the AI4Culture project (previously named AI4Europeana) is developing a platform which constitutes an online capacity building hub for the application of AI technologies in the cultural heritage sector. The platform offers access to a pool of AI-related resources (such as openly labelled datasets for training and testing AI models), a set of deployable and reusable tools, and capacity building materials. Additionally, the project customises the platform’s components so they can be reused by cultural heritage institutions in the following scenarios:

multilingual text recognition in scanned documents
multilingual subtitles generation and validation
enrichment with information extracted from images and semantic linking
machine translation for cultural heritage metadata

The role of CrossLang is to perform the project activities related to multilingual text recognition in scanned documents.

Results

The project runs from April 2023 to February 2025. You can find more information on the Project page.

Downloads

CrossLang is proud to introduce AI4culture – a new project funded by the EU’s Digital Europe Programme. We are ready contribute to this project by applying AI technologies in the Cultural Heritage sector. Download PDF

Projects

MICE

The MICE project delivers a middleware layer that improves a customised machine translation (MT) system or connects to the CEF eTranslation MT system.

Operas

In the framework of the Translations and Open Science project of the OPERAS infrastructure, we fine-tune and evaluate machine translation systems for scholarly communication.

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