Translating via an intermediate pivot language is a common practice, but the impact of the pivot language on the quality of the final translation has not often been investigated. In order to compare the effect of different pivots, we back-translate 41 English source segments via vari- ous intermediate channels (Arabic, Chinese and monolingual paraphrasing) into English. We compare the 912 English back-translations of the 41 original English segments using manual evaluation, as well as COMET and various incarnations of BLEU. We compare human from- scratch back-translations with MT back-translations and monolingual paraphrasing. A varia- tion of BLEU (Cum-2) seems to better correlate with our manual evaluation than COMET and the conventional BLEU Cum-4, but a fine-grained qualitative analysis reveals that differences between different pivot languages (Arabic and Chinese) are not captured by the automatized TQA measures.

This study investigates the impact of translation briefs and search conditions on post-editing (PE) quality produced by participants with different levels of translation proficiency. We hired five Chinese student translators and seven Japanese professional translators to conduct full post-editing (FPE) and light post-editing (LPE), as described in the translation brief, while controlling two search conditions i.e., usage of a termbase (TB) and internet search (IS). Our results show that FPE versions of the final translations tend to have less errors than LPE ver- sions. The FPE translation brief improves participants’ performance on fluency as compared to LPE, whereas the search condition of TB helps to improve participants’ performance on accuracy as compared to IS. Our findings also indicate that the occurrences of fluency errors produced by experienced translators (i.e., the Japanese participants) are more in line with the specifications addressed in translation briefs, whereas the occurrences of accuracy errors pro- duced by inexperienced translators (i.e., our Chinese participants) depend more on the search conditions.

The CRITT (Center for Research and Innovation in Translation and Translation Technology) provides a Translation Process Research Database (TPR-DB) and a rich set of summary tables and tools that help to investigate translator behavior. In this paper, we describe a new tool in the TPR-DB that converts Trados Studio keylogging data (Qualitivity) into Translog-II format and adds the converted data to the CRITT TPR-DB. The tool is also able to synchronize with the output of various eye-trackers. We describe the components of the new TPR-DB tool and highlight some of the features that it produces in the TPR-DB tables.