Direction matters: Comparing post-editing and human translation effort and quality - Sanjun Sun; Hao Wang; Yanfang Jia (PLoS ONE, 2025)
This study investigates the critical yet understudied influence of translation direction on both neural machine translation post-editing (PE) and human translation (HT) processes. While previous research has compared PE and HT, the interaction between translation mode and directionality—particularly for linguistically distant languages—remains poorly understood. We address this gap by examining how L1-L2 (Chinese-English) versus L2-L1 (English-Chinese) directionality affects translation performance across multiple dimensions. Thirty-one native Chinese translators completed both PE and HT tasks in both language directions, with their processes documented through keylogging and screen recording. Our findings reveal that PE generally outperforms HT in speed, technical efficiency, and output quality, but these advantages manifest differently depending on translation direction. The PE advantage was significantly more pronounced in the L2-L1 direction. Conversely, perceived task difficulty was primarily determined by directionality rather than translation mode, with L1-L2 translation consistently rated more challenging regardless of whether performed through PE or HT. These results demonstrate the complex interplay between translation mode and directionality, challenging the simplistic view that PE universally reduces effort compared to HT. Our findings have important implications for translator training, workflow optimization, and fair compensation models that account for both translation mode and direction.