Predicting human translation quality
Lucia Specia, Kashif Ur Rehman Shah · Conference of the Association for Machine Translation in the Americas · 2014
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.