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
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NLP Community Building - ComBi
SwissNLP would like to take concerted action to better network Swiss players from industry, science and administration in the field of Natural Language Processing (NLP). For this reason various activities are to be carried out until the end of 2025 such as expert group meetings, applied conferences, data ...
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AI4CP: AI for self-organizing Content Platform
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Towards a Voice-Based Chatbot for Language Learners (ChaLL)
We take first steps towards developing ChaLL, a voice-based chatbot that provides language learners with opportunities to practice speaking in both focused and unfocused task-based conversations and receive feedback, free from the time constraints and pressures of the traditional classroom setting. ...
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PRISM: Predicting Radicalization Events in Social Media User Timelines
The PRISM project focuses on detecting radicalization events in Social Media networks. Overall, we are interested in unveiling the mechanics that lead to the event of extremist ideology being transferred and incorporated into a social media user’s world view. Specifically, the proposed project aims to identify ...
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DOSSMA – Detection of Suspicious Social Media Activities
The DOSSMA project will investigate suspicious and malicious behaviour on social media platforms. In a first phase, we will compile an extensive survey report on the areas that are currently being researched, including the respective state-of-the-art, existing solutions and initiatives. This report will serve as a ...
Publications
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Benites de Azevedo e Souza, Fernando; von Däniken, Pius; Cieliebak, Mark,
2019.
TwistBytes - identification of Cuneiform languages and German dialects at VarDial 2019 [paper].
In:
Proceedings of the Sixth Workshop on NLP for Similar Languages, Varieties and Dialects.
6th Workshop on NLP for Similar Languages, Varieties and Dialects, VarDial 2019, Minneapolis, United States, 7 June 2019.
Ann Arbor:
Association for Computational Linguistics.
pp. 194-201.
Available from: https://doi.org/10.18653/v1/W19-1421
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Deriu, Jan Milan; Rodrigo, Alvaro; Otegi, Arantxa; Guillermo, Echegoyen; Rosset, Sophie; Agirre, Eneko; Cieliebak, Mark, eds.,
2019.
Survey on evaluation methods for dialogue.
ZHAW Zürcher Hochschule für Angewandte Wissenschaften.
Available from: https://doi.org/10.21256/zhaw-18985
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Meierhofer, Jürg; Stadelmann, Thilo; Cieliebak, Mark,
2019.
.
In:
Braschler, Martin; Stadelmann, Thilo; Stockinger, Kurt, eds.,
Applied data science : lessons learned for the data-driven business.
Cham:
Springer.
pp. 47-61.
Available from: https://doi.org/10.1007/978-3-030-11821-1_4
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Amirian, Mohammadreza; Rombach, Katharina; Tuggener, Lukas; Schilling, Frank-Peter; Stadelmann, Thilo,
2019.
Efficient deep CNNs for cross-modal automated computer vision under time and space constraints [paper].
In:
ECML-PKDD 2019, Würzburg, Germany, 16-19 September 2019.
ZHAW Zürcher Hochschule für Angewandte Wissenschaften.
Available from: https://doi.org/10.21256/zhaw-18357
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Venzin, Valentin; Deriu, Jan Milan; Didier, Orel; Cieliebak, Mark,
2019.
Fact-aware abstractive text summarization using a pointer-generator network [paper].
In:
4th Swiss Text Analytics Conference (SwissText 2019), Winterthur, June 18-19 2019.
Swisstext.
Available from: https://doi.org/10.21256/zhaw-18988