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NOAH's Corpus: Part-of-Speech Tagging for Swiss German

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Abstract (2014)

Swiss German is a dialect continuum of the Alemannic dialect group. It comprises numerous varieties used in the German-speaking part of Switzerland. Although mainly oral varieties (Mundarten), they are frequently used in written communication. On the basis of their high acceptance in the Swiss culture and with the introduction of digital communication, Swiss German has undergone a spread over all kinds of communication forms and social media. Considering the lack of standard spelling rules, this leads to a huge linguistic variability because people write the way they speak.

Such a situation is a challenging task for NLP and we would like to provide data and resources to serve as a stepping stone to automatically process texts written in these dialects. We compiled NOAH's Corpus of Swiss German Dialects consisting of various text genres, manually annotated with Part-of-Speech tags. Furthermore, we applied this corpus as training set to a statistical Part-of-Speech tagger and a dialect identification model.

Original Corpus

NOAH's Corpus of Swiss German Dialects contains five XML files. Each file contains Swiss German texts in a different text genre:

[1] http://epaper.blick.ch/webreader/baa/download/?doc=BAA280513ZH [2] http://alessandrainitaly.blogspot.ch/, http://alinesabroad.blogspot.ch/, http://anitainmexico.blogspot.ch/ [3] http://www.forum-helveticum.ch/logicio/client/forumhelveticum/file/news/SwatchJahresbericht2012.pdf [4] http://www.zuerituetsch.ch/ [5] als.wikipedia.org, downloaded: 10 April, 2012

Annotations

All texts have been tokenized and manually annotated with Part-of-Speech tags. The UPOS tags were created by a mapping from STTS to UPOS. The original tagset is described in "Compilation of a Swiss German Dialect Corpus and its Application to PoS Tagging".

Metadata

Each article in the XML files contains a title and, where known, the dialect it is written in.

Model (updated: Jan 2023)

The most recent model (Jan 2023) is available on the Huggingface Model Hub: swiss_german_pos_model

Test Set used in the ACL 2022 paper

ACL Publication: Improving Zero-Shot Cross-lingual Transfer Between Closely Related Languages by Injecting Character-Level Noise

Publications

@inproceedings{hollenstein2014compilation,
  title={Compilation of a Swiss German dialect corpus and its application to PoS tagging},
  author={Hollenstein, Nora and Aepli, No{\"e}mi},
  booktitle={Proceedings of the first workshop on applying NLP tools to similar languages, varieties and dialects},
  pages={85--94},
  year={2014}
}

@inproceedings{DBLP:conf/gldv/HollensteinA15,
  author={Nora Hollenstein and Noëmi Aepli},
  title={A Resource for Natural Language Processing of Swiss German Dialects},
  year={2015},
  cdate={1420070400000},
  pages={108-109},
  url={http://gscl2015.inf.uni-due.de/wp-content/uploads/2016/02/GSCL-201515.pdf},
  booktitle={GSCL},
  crossref={conf/gldv/2015}
}

@inproceedings{zora159152,
       booktitle = {SwissText 2018},
           month = {June},
           title = {Parsing Approaches for Swiss German},
          author = {No{\"e}mi Aepli and Simon Clematide},
       publisher = {s.n.},
            year = {2018},
        language = {english},
             url = {https://doi.org/10.5167/uzh-159152}
}


@inproceedings{aepli-sennrich-2022-improving,
    title = "Improving Zero-Shot Cross-lingual Transfer Between Closely Related Languages by Injecting Character-Level Noise",
    author = {Aepli, No{\"e}mi  and
      Sennrich, Rico},
    booktitle = "Findings of the Association for Computational Linguistics: ACL 2022",
    month = may,
    year = "2022",
    address = "Dublin, Ireland",
    publisher = "Association for Computational Linguistics",
    url = "https://aclanthology.org/2022.findings-acl.321",
    doi = "10.18653/v1/2022.findings-acl.321",
    pages = "4074--4083",
}

License

This resource is freely available for research, education and evaluation.

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