Leveraging an unprecedented corpus of newspaper and radio archives, Impresso – Media Monitoring of the Past is an interdisciplinary research project that uses machine learning to pursue a paradigm shift in the processing, semantic enrichment, representation, exploration and study of historical media across modalities, time, languages, and national borders.
Institutional frame
The impresso project is funded by the Swiss National Science Foundation (SNSF 213585) and the Luxembourg National Research Fund (FNR 17498891) as part of the Sinergia / INTER funding programmes from September 2023 until February 2027.
Applicants – The impresso project draws on the expertise of four leading institutions in digital humanities, computational linguistics and digital history from Luxembourg and Switzerland.
- Digital Humanities Laboratory (DHLAB), EPFL;
- History Department, University of Lausanne (UNIL);
- Institute of Computational Linguistics (ICL), University of Zurich;
- Centre for Contemporary and Digital History (C2DH), University of Luxembourg.
Project partners – impresso receives high-quality content from national libraries, archives, newspapers and radio broadcasters across Europe:
- Swiss National Library (BN)
- National Library of Luxembourg (BNL)
- Austrian National Library (ONB)
- Berlin State Library (SBB)
- The British Library (BL)
- French National Library (BnF)
- Hamburg State and University Library (SUB Hamburg)
- Royal Library of Belgium (KBR)
- Royal Library of the Netherlands (KB)
- Cantonal and University Library of Lausanne (BCUL)
- Swiss Radio and Television (RTS)
- Austrian Broadcasing Corporation (ORF)
- British Broadcasting Corporation (BBC)
- DeutschlandRadio
- French National Audiovisual Institute (INA)
- Netherlands Institute for Sounds and Vision (NISV)
- Le Temps
- Neue Zürcher Zeitung (NZZ)
- Entangled Media Histories Research Network for European Media Historians (EMHIS)
- Memoriav, The Swiss network for Audiovisual cultural heritage preservation
- infoclio, the Swiss portal for the historical science
Related activities
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Datasets
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Code
- https://github.com/impresso
Student projects
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Related publications
(See the publications page of the project website for a complete list).