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statworx/swiss-dialects

Dataset Card for ArchiMod Corpus Dataset Summary The ArchiMob corpus represents German linguistic varieties spoken within the territory of Switzerland. This corpus is the first electronic resource containing long samples of transcribed text in Swiss German, intended for studying the spatial distribution of morphosyntactic features and for natural language processing. Languages Swiss-German Dataset Structure Data Instances… See the full description on the dataset page: https://huggingface.co/datasets/statworx/swiss-dialects.

sourceHugging Facecc-by-nc-4.0updated 4y agoView on Hugging Face
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Dataset Card

Dataset Card for ArchiMod Corpus

Dataset Description

  • Homepage: https://wortschatz.uni-leipzig.de/en/download/Swiss%20German
  • Repository: https://huggingface.co/datasets/statworx/leipzip-swiss

Dataset Summary

The ArchiMob corpus represents German linguistic varieties spoken within the territory of Switzerland. This corpus is the first electronic resource containing long samples of transcribed text in Swiss German, intended for studying the spatial distribution of morphosyntactic features and for natural language processing.

Languages

Swiss-German

Dataset Structure

Data Instances

` { 'sentence': Sentence in Swiss-German, 'label': Dialect as category } `

Data Fields

sentence: Text as string. label: Label as string.

Data Splits

[More Information Needed]

Dataset Creation

Source Data

Initial Data Collection and Normalization

https://www.spur.uzh.ch/en/departments/research/textgroup/ArchiMob.html

Additional Information

Licensing Information

Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License

Citation Information

Scherrer, Y., T. Samardžić, E. Glaser (2019). "Digitising Swiss German -- How to process and study a polycentric spoken language". Language Resources and Evaluation. (First online)

Scherrer, Y., T. Samardžić, E. Glaser (2019). "ArchiMob: Ein multidialektales Korpus schweizerdeutscher Spontansprache". Linguistik Online, 98(5), 425-454. https://doi.org/10.13092/lo.98.5947