Tagging a Corpus of Spoken Swedish

Joakim Nivre | Department of Linguistics, Göteborg University, Sweden

Leif Grönqvist | Department of Linguistics, Göteborg University, Sweden

In this article, we present and evaluate a method for training a statistical part-of-speech tagger on data from written language and then adapting it to the requirements of tagging a corpus of transcribed spoken language, in our case spoken Swedish. This is currently a significant problem for many research groups working with spoken language, since the availability of tagged training data from spoken language is still very limited for most languages. The overall accuracy of the tagger developed for spoken Swedish is quite respectable, varying from 95% to 97% depending on the tagset used. In conclusion, we argue that the method presented here gives good tagging accuracy with relatively little effort.

Keywords: statistical part-of-speech tagging, spoken language corpora

Published online: 17 December 2001
https://doi.org/10.1075/ijcl.6.1.03niv

Cited by

Cited by 3 other publications

Allwood, Jens, Leif Grönqvist, Elisabeth Ahlsén & Magnus Gunnarsson

2003. In Current and New Directions in Discourse and Dialogue [Text, Speech and Language Technology, 22], ► pp. 1 ff.

Bondi Johannessen, Janne

2017. In Handbook of Linguistic Annotation, ► pp. 1303 ff.

Osimk-Teasdale, Ruth & Nora Dorn

2016. Accounting for ELF. International Journal of Corpus Linguistics 21:3 ► pp. 372 ff.

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