Time efficiency is paramount for the localisation industry, which demands ever-faster turnaround times. However, translation speed is largely underresearched, and there is a lack of clarity about how language service providers (LSPs) can evaluate the performance of their post-editing (PE) and human translation (HT) services. This study constitutes the first large-scale investigation of translation and revision speed in HT and in the PE of neural machine translation, based on real-world data from an LSP. It uses an exploratory data analysis approach to investigate data for 90 million words translated by 879 linguists across 11 language pairs, over 2.5 years. The results of this research indicate that (a) PE is usually but not always faster than HT; (b) average speed values may be misleading; (c) translation speed is highly variable; and (d) edit distance cannot be used as a proxy for post-editing productivity, because it does not correlate strongly with speed.

翻译：时间效率对本地化行业至关重要，该行业要求日益缩短的交付周期。然而，翻译速度在很大程度上尚未得到充分研究，语言服务提供商（LSP）如何评估其译后编辑（PE）和人工翻译（HT）服务的绩效也不够清晰。本研究基于一家语言服务提供商的实际数据，首次大规模调查了人工翻译与神经机器翻译译后编辑中的翻译和修订速度。研究采用探索性数据分析方法，对来自11个语言对、879名语言学家在2.5年时间内翻译的9000万词汇数据进行了分析。结果表明：（a）译后编辑通常但不总是比人工翻译更快；（b）平均速度值可能具有误导性；（c）翻译速度具有高度变异性；（d）编辑距离不能作为译后编辑生产力的替代指标，因为它与速度的相关性不强。