Natural Language Processing Group | ZHAW School of Engineering

“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.”

Professor Dr Mark Clieliebak

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

Prof. Dr. Mark Cieliebak

+41 (0) 58 934 72 39
mark.cieliebak@zhaw.ch

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

Deriu, Jan Milan; Cieliebak, Mark,

2016.

Sentiment analysis using convolutional neural networks with multi-task training and distant supervision on italian tweets [paper].

In:

Basili, Roberto; Montemagni, Simonetta, eds.,

Proceedings of Third Italian Conference on Computational Linguistics (CLiC-it 2016) & Fifth Evaluation Campaign of Natural Language Processing and Speech Tools for Italian. Final Workshop (EVALITA 2016).

Fifth Evaluation Campaign of Natural Language Processing and Speech Tools for Italian, Napoli, Italy, 5-7 December 2016.

Italian Journal of Computational Linguistics.

Available from: https://doi.org/10.21256/zhaw-1527
Cieliebak, Mark; Egger, Dominic; Uzdilli, Fatih,

2016.

Twitter can help to find adverse drug reactions.

ERCIM News.

104.
Schutzbach, Daniel; Uzdilli, Fatih; Cieliebak, Mark,

2015.

Back to the Future : Time-Travelling-Debugger als Alternative zu klassischen Debuggern.

Java Magazin.

2015(11), pp. 18-22.
Arnold, Marek; Cieliebak, Mark; Stadelmann, Thilo; Stampfli, Jan; Uzdilli, Fatih,

2015.

PANOPTES : automated article segmentation of newspaper pages for "Real Time Print Media Monitoring“ [poster].

In:

Proceedings of SGAICO Annual Assembly and Workshop 2015.

SGAICO Annual Assembly and Workshop 2015, Geneva, 12 November 2015.

Swiss Group for Artificial Intelligence and Cognitive Science.

Available from: https://doi.org/10.21256/zhaw-7739
Uzdilli, Fatih; Jaggi, Martin; Egger, Dominic; Julmy, Pascal; Derczynski, Leon; Cieliebak, Mark,

2015.

Swiss-Chocolate : combining flipout regularization and random forests with artificially built subsystems to boost text-classification for sentiment [paper].

In:

Proceedings of the 9th International Workshop on Semantic Evaluation (SemEval 2015), Denver, Colorado, June 4-5, 2015.

International Workshop on Semantic Evaluation (SemEval-2014), Dublin, Irland, 23-24 August 2014.

Association for Computational Linguistics.

pp. 608-612.

Available from: https://doi.org/10.18653/v1/S15-2101