Towards Shared Datasets for Normalization Research

Orphée De Clercq, Sarah Schulz, Bart Desmet, Véronique Hoste

Abstract
In this paper we present a Dutch and English dataset that can serve as a gold standard for evaluating text normalization approaches. With the combination of text messages, message board posts and tweets, these datasets represent a variety of user generated content. All data was manually normalized to their standard form using newly-developed guidelines. We perform automatic lexical normalization experiments on these datasets using statistical machine translation techniques. We focus on both the word and character level and find that we can improve the BLEU score with ca. 20% for both languages. In order for this user generated content data to be released publicly to the research community some issues first need to be resolved. These are discussed in closer detail by focussing on the current legislation and by investigating previous similar data collection projects. With this discussion we hope to shed some light on various difficulties researchers are facing when trying to share social media data.
Anthology ID:
L14-1574
Volume:
Proceedings of the Ninth International Conference on Language Resources and Evaluation (LREC'14)
Month:
May
Year:
2014
Address:
Reykjavik, Iceland
Editors:
Nicoletta Calzolari, Khalid Choukri, Thierry Declerck, Hrafn Loftsson, Bente Maegaard, Joseph Mariani, Asuncion Moreno, Jan Odijk, Stelios Piperidis
Venue:
LREC
SIG:
Publisher:
European Language Resources Association (ELRA)
Note:
Pages:
1218–1223
Language:
URL:
http://www.lrec-conf.org/proceedings/lrec2014/pdf/733_Paper.pdf
DOI:
Bibkey:
Cite (ACL):
Orphée De Clercq, Sarah Schulz, Bart Desmet, and Véronique Hoste. 2014. Towards Shared Datasets for Normalization Research. In Proceedings of the Ninth International Conference on Language Resources and Evaluation (LREC'14), pages 1218–1223, Reykjavik, Iceland. European Language Resources Association (ELRA).
Cite (Informal):
Towards Shared Datasets for Normalization Research (De Clercq et al., LREC 2014)
Copy Citation:
PDF:
http://www.lrec-conf.org/proceedings/lrec2014/pdf/733_Paper.pdf
PDF Search