Article | Proceedings of the 20th Nordic Conference of Computational Linguistics, NODALIDA 2015, May 11-13, 2015, Vilnius, Lithuania | Enriching the Swedish Sign Language Corpus with Part of Speech Tags Using Joint Bayesian Word Alignment and Annotation Transfer
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Title:
Enriching the Swedish Sign Language Corpus with Part of Speech Tags Using Joint Bayesian Word Alignment and Annotation Transfer
Author:
Robert Östling: Department of Linguistics, Stockholm University, Stockholm, Sweden Carl Börstell: Department of Linguistics, Stockholm University, Stockholm, Sweden Lars Wallin: Department of Linguistics, Stockholm University, Stockholm, Sweden
Download:
Full text (pdf)
Year:
2015
Conference:
Proceedings of the 20th Nordic Conference of Computational Linguistics, NODALIDA 2015, May 11-13, 2015, Vilnius, Lithuania
Issue:
109
Article no.:
034
Pages:
263-268
No. of pages:
6
Publication type:
Abstract and Fulltext
Published:
2015-05-06
ISBN:
978-91-7519-098-3
Series:
Linköping Electronic Conference Proceedings
ISSN (print):
1650-3686
ISSN (online):
1650-3740
Series:
NEALT Proceedings Series
Publisher:
Linköping University Electronic Press, Linköpings universitet


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We have used a novel Bayesian model of joint word alignment and part of speech (PoS) annotation transfer to enrich the Swedish Sign Language Corpus with PoS tags. The annotations were then hand-corrected in order to both improve annotation quality for the corpus, and allow the empirical evaluation presented herein.

Proceedings of the 20th Nordic Conference of Computational Linguistics, NODALIDA 2015, May 11-13, 2015, Vilnius, Lithuania

Author:
Robert Östling, Carl Börstell, Lars Wallin
Title:
Enriching the Swedish Sign Language Corpus with Part of Speech Tags Using Joint Bayesian Word Alignment and Annotation Transfer
References:

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Proceedings of the 20th Nordic Conference of Computational Linguistics, NODALIDA 2015, May 11-13, 2015, Vilnius, Lithuania

Author:
Robert Östling, Carl Börstell, Lars Wallin
Title:
Enriching the Swedish Sign Language Corpus with Part of Speech Tags Using Joint Bayesian Word Alignment and Annotation Transfer
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