Papers by Inguna Skadiņa
The European Language Technology Landscape in 2020: Language-Centric and Human-Centric AI for Cross-Cultural Communication in Multilingual Europe (2020.lrec-1)
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Georg Rehm, Katrin Marheinecke, Stefanie Hegele, Stelios Piperidis, Kalina Bontcheva, Jan Hajič, Khalid Choukri, Andrejs Vasiļjevs, Gerhard Backfried, Christoph Prinz, José Manuel Gómez-Pérez, Luc Meertens, Paul Lukowicz, Josef van Genabith, Andrea Lösch, Philipp Slusallek, Morten Irgens, Patrick Gatellier, Joachim Köhler, Laure Le Bars, Dimitra Anastasiou, Albina Auksoriūtė, Núria Bel, António Branco, Gerhard Budin, Walter Daelemans, Koenraad De Smedt, Radovan Garabík, Maria Gavriilidou, Dagmar Gromann, Svetla Koeva, Simon Krek, Cvetana Krstev, Krister Lindén, Bernardo Magnini, Jan Odijk, Maciej Ogrodniczuk, Eiríkur Rögnvaldsson, Mike Rosner, Bolette Pedersen, Inguna Skadiņa, Marko Tadić, Dan Tufiș, Tamás Váradi, Kadri Vider, Andy Way, François Yvon
| Challenge: | Language Technologies (LTs) are a powerful means to break down language barriers impacting business, cross-lingual and cross-cultural communication in Europe. |
| Approach: | They present an overview of the European LT landscape and the current state of play in industry and the LT market. |
| Outcome: | The present study outlines funding programmes, activities, actions and challenges in the different countries with regard to LT, including the current state of play in industry and the LT market. |
MultiLeg: Dataset for Text Sanitisation in Less-resourced Languages (2024.lrec-main)
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| Challenge: | Text sanitization is the task of detecting and removing personal information from the text. |
| Approach: | They propose a dataset for multilingual named entities that can be used for text sanitization. |
| Outcome: | The proposed dataset is available in 8 languages and contains 3082 parallel text segments for each language. |
The Competitiveness Analysis of the European Language Technology Market (2020.lrec-1)
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Andrejs Vasiļjevs, Inguna Skadiņa, Indra Samite, Kaspars Kauliņš, Ēriks Ajausks, Jūlija Meļņika, Aivars Bērziņš
| Challenge: | The study focuses on three LT areas of the greatest interest for the ECmachine translation (MT), speech technology, and cross-lingual search. |
| Approach: | This paper presents the key results of a competitiveness analysis of the European language technology market for three areas – Machine Translation, speech technology, and cross-lingual search. |
| Outcome: | The study focuses on three LT areas of the greatest interest for the ECmachine translation (MT), speech technology, and cross-lingual search. |
Assessing Multilinguality of Publicly Accessible Websites (2022.lrec-1)
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| Challenge: | multilingualism on the Web is a problem not only at the world level, but also at the European and regional level. |
| Approach: | They propose a tool that automatically analyses the language diversity of the Web and propose indicators and methodologies to measure multilingualism of European websites. |
| Outcome: | The proposed tool can be independently run at set intervals and concludes that multilingualism on the Web is still a problem not only at the world level, but also at the European and regional level. |
Latvian National Corpora Collection – Korpuss.lv (2022.lrec-1)
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Baiba Saulite, Roberts Darģis, Normunds Gruzitis, Ilze Auzina, Kristīne Levāne-Petrova, Lauma Pretkalniņa, Laura Rituma, Peteris Paikens, Arturs Znotins, Laine Strankale, Kristīne Pokratniece, Ilmārs Poikāns, Guntis Barzdins, Inguna Skadiņa, Anda Baklāne, Valdis Saulespurēns, Jānis Ziediņš
| Challenge: | Latvian National Corpora Collection (LNCC) is a multi-institutional and multi-project effort supporting the Latvian language research and language modelling. |
| Approach: | They propose to use Latvian corpora for linguistic research and language modelling. |
| Outcome: | LNCC is a multi-institutional and multi-project effort supported by the Digital Humanities and Language Technology communities in Latvia. |