Lexical similarity can distinguish between automatic and manual translations

Agam Patel, Dragomir R. Radev


Abstract
We consider the problem of identifying automatic translations from manual translations of the same sentence. Using two different similarity metrics (BLEU and Levenshtein edit distance), we found out that automatic translations are closer to each other than they are to manual translations. We also use phylogenetic trees to provide a visual representation of the distances between pairs of individual sentences in a set of translations. The differences in lexical distance are statistically significant, both for Chinese to English and for Arabic to English translations.
Anthology ID:
L06-1129
Volume:
Proceedings of the Fifth International Conference on Language Resources and Evaluation (LREC’06)
Month:
May
Year:
2006
Address:
Genoa, Italy
Editors:
Nicoletta Calzolari, Khalid Choukri, Aldo Gangemi, Bente Maegaard, Joseph Mariani, Jan Odijk, Daniel Tapias
Venue:
LREC
SIG:
Publisher:
European Language Resources Association (ELRA)
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Pages:
Language:
URL:
http://www.lrec-conf.org/proceedings/lrec2006/pdf/235_pdf.pdf
DOI:
Bibkey:
Cite (ACL):
Agam Patel and Dragomir R. Radev. 2006. Lexical similarity can distinguish between automatic and manual translations. In Proceedings of the Fifth International Conference on Language Resources and Evaluation (LREC’06), Genoa, Italy. European Language Resources Association (ELRA).
Cite (Informal):
Lexical similarity can distinguish between automatic and manual translations (Patel & Radev, LREC 2006)
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PDF:
http://www.lrec-conf.org/proceedings/lrec2006/pdf/235_pdf.pdf