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Language AI

“Language AI is transforming how humans interact with technology. We explore how machines can understand, process, and generate language – and turn these advances into robust solutions for real-world applications.”

Professor Dr Mark Cieliebak

Expertise and Services

Expertise

  • Dialogue systems
  • Speech processing
  • Social media analysis
  • Evaluation of Large Language Models (LLMs)

The Language AI 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

Team

Projects

Publications

  • 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.

  • 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

  • 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.

  • 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.

  • 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/10.21256/zhaw-3872