A Database for Measuring Linguistic Information Content

Richard Sproat, Bruno Cartoni, HyunJeong Choe, David Huynh, Linne Ha, Ravindran Rajakumar, Evelyn Wenzel-Grondie


Abstract
Which languages convey the most information in a given amount of space? This is a question often asked of linguists, especially by engineers who often have some information theoretic measure of “information” in mind, but rarely define exactly how they would measure that information. The question is, in fact remarkably hard to answer, and many linguists consider it unanswerable. But it is a question that seems as if it ought to have an answer. If one had a database of close translations between a set of typologically diverse languages, with detailed marking of morphosyntactic and morphosemantic features, one could hope to quantify the differences between how these different languages convey information. Since no appropriate database exists we decided to construct one. The purpose of this paper is to present our work on the database, along with some preliminary results. We plan to release the dataset once complete.
Anthology ID:
L14-1397
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:
967–974
Language:
URL:
http://www.lrec-conf.org/proceedings/lrec2014/pdf/47_Paper.pdf
DOI:
Bibkey:
Cite (ACL):
Richard Sproat, Bruno Cartoni, HyunJeong Choe, David Huynh, Linne Ha, Ravindran Rajakumar, and Evelyn Wenzel-Grondie. 2014. A Database for Measuring Linguistic Information Content. In Proceedings of the Ninth International Conference on Language Resources and Evaluation (LREC'14), pages 967–974, Reykjavik, Iceland. European Language Resources Association (ELRA).
Cite (Informal):
A Database for Measuring Linguistic Information Content (Sproat et al., LREC 2014)
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PDF:
http://www.lrec-conf.org/proceedings/lrec2014/pdf/47_Paper.pdf