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,
2019.
Towards integration of statistical hypothesis tests into deep neural networks [paper].
In:
Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics.
57th Annual Meeting of the Association for Computational Linguistics, Florence, Italy, 28 July - 2 August 2019.
Association for Computational Linguistics.
pp. 5551-5557.
Available from: https://doi.org/10.18653/v1/P19-1557
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Cieliebak, Mark; Galibert, Olivier; Deriu, Jan Milan,
2019.
Towards understanding lifelong learning for dialogue systems [paper].
In:
IWSDS 2019 Proceedings.
IWSDS 2019 : International Workshop on Spoken Dialogue Systems Technology, Siracusa, Italy, Apr 24, 2019 - Apr 26, 2019.
IWSDS.
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Elezi, Ismail; Tuggener, Lukas; Pelillo, Marcello; Stadelmann, Thilo,
2018.
DeepScores and Deep Watershed Detection : current state and open issues [paper].
In:
Proceedings of the 1st International Workshop on Reading Music Systems.
1st International Workshop on Reading Music Systems at ISMIR 2018, Paris, France, 20 September 2018.
Paris:
Society for Music Information Retrieval.
pp. 13-14.
Available from: https://doi.org/10.21256/zhaw-4777
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Siddiqui, Nadina; Metzler, Linus; Tuggener, Don; Cieliebak, Mark,
2018.
A framework for text analytics with visual exploration and machine learning [poster].
In:
Fachkonferenz Technik, Architektur und Life Sciences (FTAL), Lugano, 18.-19. Oktober 2018.
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von Grünigen, Dirk; Benites de Azevedo e Souza, Fernando; Pradarelli, Beatrice; Magid, Amani; Cieliebak, Mark,
2018.
Best practices in e-assessments with a special focus on cheating prevention [paper].
In:
Proceedings of 2018 IEEE Global Engineering Education Conference (EDUCON).
2018 IEEE Global Engineering Education Conference (EDUCON18), Tenerife, 17-20 April 2018.
IEEE.
pp. 893-899.
Available from: https://doi.org/10.1109/EDUCON.2018.8363325