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
-
Stadelmann, Thilo; Amirian, Mohammadreza; Arabaci, Ismail; Arnold, Marek; Duivesteijn, Gilbert François; Elezi, Ismail; Geiger, Melanie; Lörwald, Stefan; Meier, Benjamin Bruno; Rombach, Katharina; Tuggener, Lukas,
2018.
Deep learning in the wild [paper].
In:
Artificial Neural Networks in Pattern Recognition.
8th IAPR TC3 Workshop on Artificial Neural Networks in Pattern Recognition (ANNPR), Siena, Italy, 19-21 September 2018.
Springer.
pp. 17-38.
Lecture Notes in Computer Science ; 11081.
Available from: https://doi.org/10.1007/978-3-319-99978-4_2
-
Tuggener, Lukas; Elezi, Ismail; Schmidhuber, Jürgen; Stadelmann, Thilo,
2018.
Deep watershed detector for music object recognition [paper].
In:
Proceedings of the 19th International Society for Music Information Retrieval Conference.
19th International Society for Music Information Retrieval Conference, Paris, 23-27 September 2018.
Paris:
Society for Music Information Retrieval.
Available from: https://doi.org/10.21256/zhaw-3760
-
Tuggener, Lukas; Elezi, Ismail; Schmidhuber, Jürgen; Pelillo, Marcello; Stadelmann, Thilo,
2018.
DeepScores : a dataset for segmentation, detection and classification of tiny objects [paper].
In:
2018 24th International Conference on Pattern Recognition (ICPR).
24th International Conference on Pattern Recognition (ICPR 2018), Beijing, China, 20-28 August 2018.
IEEE.
pp. 1-6.
Available from: https://doi.org/10.1109/ICPR.2018.8545307
-
Sugisaki, Kyoko; Tuggener, Don,
2018.
German compound splitting using the compound productivity of morphemes [paper].
In:
Barbaresi, Adrien; Biber, Hanno; Neubarth, Friedrich; Osswald, Rainer, eds.,
14th Conference on Natural Language Processing - KONVENS 2018.
14th Conference on Natural Language Processing (KONVENS 2018), Vienna, Austria, 19-21 September 2018.
Austrian Academy of Sciences Press.
pp. 141-147.
Available from: https://doi.org/10.21256/zhaw-4974
-
Agirre, Eneko; Marchand, Sarah; Rosset, Sophie; Peñas, Anselmo; Cieliebak, Mark,
2018.
LIHLITH : improving communication skills of robots through lifelong learning.
ERCIM News.
2018(114), pp. 12.
Available from: https://ercim-news.ercim.eu/images/stories/EN114/EN114-web.pdf