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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Deriu, Jan Milan; Cieliebak, Mark,
2017.
End-to-end trainable system for enhancing diversity in natural language generation [paper].
In:
End-to-End Natural Language Generation Challenge (E2E NLG), 2017.
ZHAW Zürcher Hochschule für Angewandte Wissenschaften.
Available from: https://doi.org/10.21256/zhaw-4889
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Graf, Hans Daniel; Koc, Yusuf; Panighetti, Sandro; Togni, Matteo; von Grünigen, Dirk; Weilenmann, Martin; Xhoxhaj, Erland; Zürrer, Daniel; Benites de Azevedo e Souza, Fernando; Deriu, Jan Milan; Neureiter, Nico; von Däniken, Pius; Cieliebak, Mark; Eich, Walter; Neuhaus, Stephan; Stockinger, Kurt,
2017.
Four different ways to build a chatbot about movies [poster].
In:
SwissText 2017: 2nd Swiss Text Analytics Conference, Winterthur, 9. Juni 2017.
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Meier, Benjamin; Stadelmann, Thilo; Stampfli, Jan; Arnold, Marek; Cieliebak, Mark,
2017.
Fully convolutional neural networks for newspaper article segmentation [paper].
In:
Proceedings of the 14th IAPR International Conference on Document Analysis and Recognition (ICDAR).
14th IAPR International Conference on Document Analysis and Recognition (ICDAR 2017), Kyoto Japan, 13-15 November 2017.
Kyoto:
CPS.
Available from: https://doi.org/10.21256/zhaw-1533
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Benites de Azevedo e Souza, Fernando; Cieliebak, Mark,
2017.
Hierarchical classificaion for news articles [poster].
In:
SwissText 2017: 2nd Swiss Text Analytics Conference, Winterthur, 9. Juni 2017.
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Cieliebak, Mark; Magid, Amani; Pradarelli, Beatrice,
2017.
How to throw chocolate at students : a survey of extrinsic means for increased audience attention [paper].
In:
Global Engineering Education Conference (EDUCON).
Global Engineering Education Conference (EDUCON), Athens, Greece, 25-28 April 2017.
IEEE.
pp. 199-203.
Available from: https://doi.org/10.1109/EDUCON.2017.7942847