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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Leuschen, Lara; Betzler, Diana; Fredersdorf, Frederic; Rebitzer, Fabian; Cieliebak, Mark; Benites de Azevedo e Souza, Fernando,
2020.
Digitale Kommunikationsstrategien für den Kultursektor der Bodenseeregion.
Kreuzlingen:
Internationale Bodensee Hochschule.
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Campos, Jon Ander; Otegi, Arantxa; Soroa, Aitor; Deriu, Jan Milan; Cieliebak, Mark; Agirre, Eneko,
2020.
DoQA : accessing domain-specific FAQs via conversational QA [paper].
In:
Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics.
58th Annual Meeting of the Association for Computational Linguistics (ACL 2020), online, 5-10 July 2020.
Association for Computational Linguistics.
pp. 7302-7314.
Available from: https://doi.org/10.18653/v1/2020.acl-main.652
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Cieliebak, Mark; Keck Frei, Andrea,
2020.
Flipped Classroom in der Hochschullehre einsetzen
.
In:
Bachmann, Heinz, ed.,
Hochschullehre variantenreich gestalten : Kompetenzorientierte Hochschullehre – Ansätze, Methoden und Beispiele.
Bern:
hep.
Forum Hochschuldidaktik und Erwachsenenbildung ; 4.
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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.