Natural Language Processing Group
“We combine foundational research with industrial applications to build new and innovative products and services, while at the same time exploring the necessary ethical and social boundaries.”
Fields of expertise
- Text analytics
- Dialogue systems
- Speech processing
The NLP research team develops technologies for the analysis, understanding and generation of speech and text. We combine methods from linguistics, natural language processing (NLP) and artificial intelligence to enable natural language communication between humans and machines. In our research, we work on topics such as text classification (e.g. sentiment analysis), chatbots/dialogue systems, text summarization, speech-to-text, speaker diarization and natural language generation. The group particularly focuses on Swiss German speech and text processing.
Services
- Insight: keynotes, trainings
- AI consultancy: workshops, expert support, advice, technology assessment
- Research and development: small to large-scale collaborative projects, third party-funded research, student projects, commercially applicable prototypes
Team
Head of Research Group
Projects
Unfortunately, no list of projects can be displayed here at the moment. Until the list is available again, the project search on the ZHAW homepage can be used.
Publications
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Aghaebrahimian, Ahmad; Cieliebak, Mark,
2020.
Named entity disambiguation at scale [paper].
In:
Schilling, Frank-Peter; Stadelmann, Thilo, eds.,
Artificial Neural Networks in Pattern Recognition.
9th IAPR TC 3 Workshop on Artificial Neural Networks for Pattern Recognition (ANNPR'20), Winterthur, Switzerland, 2-4 September 2020.
Cham:
Springer.
pp. 102-110.
Lecture Notes in Computer Science ; 12294.
Available from: https://doi.org/10.1007/978-3-030-58309-5_8
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Büchi, Matthias,
2020.
Speech recognition component for search-oriented conversational artificial intelligence.
Winterthur:
ZHAW Zürcher Hochschule für Angewandte Wissenschaften.
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Deriu, Jan Milan; Rodrigo, Alvaro; Otegi, Arantxa; Echegoyen, Guillermo; Rosset, Sophie; Agirre, Eneko; Cieliebak, Mark,
2020.
Survey on evaluation methods for dialogue systems.
Artificial Intelligence Review.
54(1), pp. 755-810.
Available from: https://doi.org/10.1007/s10462-020-09866-x
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Cieliebak, Mark; Tuggener, Don; Benites, Fernando, eds.,
2019.
Proceedings of the 4th edition of the Swiss Text Analytics Conference.
SwissText 2019, Winterthur, 18-19 June 2019.
CEUR Workshop Proceedings.
.
Available from: http://ceur-ws.org/Vol-2458/
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Tuggener, Lukas; Amirian, Mohammadreza; Rombach, Katharina; Lörwald, Stefan; Varlet, Anastasia; Westermann, Christian; Stadelmann, Thilo,
2019.
Automated machine learning in practice : state of the art and recent results [paper].
In:
2019 6th Swiss Conference on Data Science (SDS).
6th Swiss Conference on Data Science (SDS), Bern, 14. Juni 2019.
IEEE.
pp. 31-36.
Available from: https://doi.org/10.1109/SDS.2019.00-11