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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Platform Meaning@Work
We are developing a digital platform called “Meaning@Work”, which supports employees in shaping their work and careers in a meaningful way.
ongoing, 03/2025 - 02/2028
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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,…
ongoing, 12/2023 - 01/2026
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AI for self-organizing Content Platform (AI4CP)
completed, 05/2023 - 11/2023
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Towards a Voice-Based Chatbot for Language Learners (ChaLL) (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.
completed, 02/2023 - 07/2024
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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…
completed, 04/2022 - 02/2023
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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…
completed, 05/2021 - 12/2021
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Speech-to-Text for Swiss German
completed, 02/2021 - 02/2022
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Virtual Kids - Virtual characters to improve the quality of child interrogations
If children are questioned in preliminary proceedings about their own experiences or observations relevant to criminal law, it depends decisively on the quality of the questioning whether their statements can be used in criminal proceedings or whether decisions can be made on this basis and…
completed, 04/2020 - 04/2024
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AuSuM – Automatic Supply Chain Monitoring
The project implements an online service for companies to monitor suppliers for violations ofenvironmental, social, or governance norms. To do so, a vast variety of sources, such as news outlets, is monitored using machine learning and natural language processing with near human-level accuracy.
completed, 12/2018 - 05/2021
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Pre-Study on Generation of Hockey News
Tamedia would like to develop a software system that automatically generates news articles from hockey game data.ZHAW will explore the different state-of-the-art technologies to evaluate the feasibility of developing a natural language system that generates rich contextual ice hockey game report…
completed, 10/2018 - 12/2019
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Digital communication strategies for the cultural sector in the Lake Constance region
This research project will investigate how a communication strategy for the marketing and communication of the diverse cultural activities and sites in the Lake Constance region could be shaped.For a sustainable strategy development the digitization of the communication, by which also the cultural…
completed, 07/2018 - 06/2020
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Call-E – Virtual Call Agent
The industrial project partner offers online brokering of loans, mortgages and insurances. The brokering process involves several phone calls of a call agent with a potential client. This is time-consuming and highly repetitive. For this reason, we want to develop a dialogue system which can take…
completed, 06/2018 - 05/2020
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SCAI – Smart Contract Analytics using Artificial Intelligence
In the SCAI project, ZHAW and legartis investigate how content of contracts can automatically be evaluated legally by applying methods from the areas of Natural Language Processing and Deep Learning.
completed, 05/2018 - 05/2020
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Natural Language Processing for Tumor Classification (NLP4TC)
Entry, discharge, radiology and pathology reports and other clinical documents are a valuable resource to be harvested for precision medicine. They are typically stored in a free text format, only little structure is imposed and terminology is heterogeneous. We will apply natural language…
completed, 05/2018 - 12/2019
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Libra: A One-Tool Solution for MLD4 Compliance
Compared with earlier regulations, the 4th European Money Laundering Directive (MLD4) imposes rigorously increased requirements. It compels obliged entities to conduct in depth screenings of customers and their associations. The Libra Project aims at providing a one tool solution for meeting MLD4…
completed, 09/2016 - 05/2019
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DeepText: Intelligent Text Analysis with Deep Learning
DeepText develops a software framework to automatically analyse texts in order to extract important information. The framework comprises modern algorithms from the field of machine learning (deep learning) that are better at analyzing texts than traditional approaches. They can for example be used…
completed, 09/2016 - 02/2018
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Automated Article Segmentation of Newspaper Pages for "Real Time Print Media Monitoring" (PANOPTES) (PANOPTES)
The new product of ARGUS DATA INSIGHTS Schweiz AG "Real Time Print Media Monitoring" is an automated pipeline. It identifies relevant articles in print media, extracts them and sends them to the customers in real-time. Core of this project is the automated segmentation of full newspaper pages into…
completed, 07/2015 - 09/2017
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AUGEST - Automatic Generation of Regression Tests
We are investigating how to use new logging tools for Java programs to automatically generate regression test data and regression tests for productive systems. This is intended to minimize the risk and effort involved in refactoring software. The key points of the project are: 1. Performance…
completed, 08/2014 - 12/2015
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Didactic Comparison between Traditional Teaching and Flipped Classroom
Evaluation "Flipped Classroom"
completed, 12/2013 - 12/2014
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SODES – Swiss Open Data Exploration System
In recent years, national and international institutions, governments and NGOs have made large amounts of data publicly available: there exist literally thousands of open data sources, with temperature measurements, stock market prices, population and income statistics etc. However, most open data…
completed, 12/2013 - 07/2014
Publications
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2014.
Flip your classroom : but be aware!.
Lifelong Learning in Europe.
2014(4).
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Dürr, Oliver; Uzdilli, Fatih; Cieliebak, Mark,
2014.
JOINT_FORCES : unite competing sentiment classifiers with random forest[paper].
In:
Proceedings of the International Workshop on Semantic Evaluation (SemEval-2014).
International Workshop on Semantic Evaluation (SemEval-2014), Dublin, Irland, 23-24 August 2014.
Association for Computational Linguistics.
pp. 366-369.
Available from: https://doi.org/10.21256/zhaw-3779
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Cieliebak, Mark; Dürr, Oliver; Uzdilli, Fatih,
2014.
Meta-classifiers easily improve commercial sentiment detection tools[paper].
In:
Proceedings of the 9th International Conference on Language Resources and Evaluation (LREC 2014).
9th International Conference on Language Resources and Evaluation, Reykjavik, Iceland, 26-31 May 2014.
Association for Computational Linguistics.
pp. 3943-3947.
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Jaggi, Martin; Uzdilli, Fatih; Cieliebak, Mark,
2014.
Swiss-chocolate : sentiment detection using sparse SVMs and part-of-speech n-grams[paper].
In:
Proceedings of the International Workshop on Semantic Evaluation (SemEval-2014).
International Workshop on Semantic Evaluation (SemEval-2014), Dublin, Irland, 23-24 August 2014.
Association for Computational Linguistics.
pp. 601-604.
Available from: https://doi.org/10.21256/zhaw-3780
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Cieliebak, Mark; Dürr, Oliver; Uzdilli, Fatih,
2013.
Potential and limitations of commercial sentiment detection tools[paper].
In:
Proceedings of the First International Workshop on Emotion and Sentiment in Social and Expressive Media: approaches and perspectives from AI (ESSEM 2013).
First International Workshop on Emotion and Sentiment in Social and Expressive Media (ESSEM 2013), Turin, Italy, 3 December 2013.
RWTH Aachen.
pp. 47-58.
CEUR Workshop Proceedings ; 1096.
Available from: http://ceur-ws.org/Vol-1096/paper4.pdf