Measuring MT Adequacy Using Latent Semantic Analysis

Florence Reeder


Abstract
Translation adequacy is defined as the amount of semantic content from the source language document that is conveyed in the target language document. As such, it is more difficult to measure than intelligibility since semantic content must be measured in two documents and then compared. Latent Semantic Analysis is a content measurement technique used in language learner evaluation that exhibits characteristics attractive for re-use in machine translation evaluation (MTE). This experiment, which is a series of applications of the LSA algorithm in various configurations, demonstrates its usefulness as an MTE metric for adequacy. In addition, this experiment lays the groundwork for using LSA as a method to measure the accuracy of a translation without reliance on reference translations.
Anthology ID:
2006.amta-papers.20
Volume:
Proceedings of the 7th Conference of the Association for Machine Translation in the Americas: Technical Papers
Month:
August 8-12
Year:
2006
Address:
Cambridge, Massachusetts, USA
Venue:
AMTA
SIG:
Publisher:
Association for Machine Translation in the Americas
Note:
Pages:
176–184
Language:
URL:
https://aclanthology.org/2006.amta-papers.20
DOI:
Bibkey:
Cite (ACL):
Florence Reeder. 2006. Measuring MT Adequacy Using Latent Semantic Analysis. In Proceedings of the 7th Conference of the Association for Machine Translation in the Americas: Technical Papers, pages 176–184, Cambridge, Massachusetts, USA. Association for Machine Translation in the Americas.
Cite (Informal):
Measuring MT Adequacy Using Latent Semantic Analysis (Reeder, AMTA 2006)
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PDF:
https://aclanthology.org/2006.amta-papers.20.pdf