Predicting human translation quality

Lucia Specia, Kashif Shah


Abstract
We present a first attempt at predicting the quality of translations produced by human, professional translators. We examine datasets annotated for quality at sentence- and word-level for four language pairs and provide experiments with prediction models for these datasets. We compare the performance of such models against that of models built from machine translations, highlighting a number of challenges in estimating quality and detecting errors in human translations.
Anthology ID:
2014.amta-researchers.22
Volume:
Proceedings of the 11th Conference of the Association for Machine Translation in the Americas: MT Researchers Track
Month:
October 22-26
Year:
2014
Address:
Vancouver, Canada
Venue:
AMTA
SIG:
Publisher:
Association for Machine Translation in the Americas
Note:
Pages:
288–300
Language:
URL:
https://aclanthology.org/2014.amta-researchers.22
DOI:
Bibkey:
Cite (ACL):
Lucia Specia and Kashif Shah. 2014. Predicting human translation quality. In Proceedings of the 11th Conference of the Association for Machine Translation in the Americas: MT Researchers Track, pages 288–300, Vancouver, Canada. Association for Machine Translation in the Americas.
Cite (Informal):
Predicting human translation quality (Specia & Shah, AMTA 2014)
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PDF:
https://aclanthology.org/2014.amta-researchers.22.pdf