mlsanityData to 14 Oct 2026

Assessing Post-editing Effort in the English-Hindi Direction

arXiv 2112.09841 ↗First posted 18 Dec 2021cs.CLcited by 1

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Abstract (arXiv)

We present findings from a first in-depth post-editing effort estimation study in the English-Hindi direction along multiple effort indicators. We conduct a controlled experiment involving professional translators, who complete assigned tasks alternately, in a translation from scratch and a post-edit condition. We find that post-editing reduces translation time (by 63%), utilizes fewer keystrokes (by 59%), and decreases the number of pauses (by 63%) when compared to translating from scratch. We further verify the quality of translations thus produced via a human evaluation task in which we do not detect any discernible quality differences.

Key facts. Cited by 1 paper in the map (data through 14 Oct 2026). Builds on 3 of its 30 references that are in the map. First posted on arXiv 18 Dec 2021.

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3 of 30 references.

References · 3

  1. 2017Attention Is All You Needcited by 60,361
  2. 2014Neural Machine Translation by Jointly Learning to Align and Translatecited by 4,548
  3. 2019Post-editing Productivity with Neural Machine Translation: An Empirical Assessment of Speed and Quality in the Banking and Finance Domaincited by 7

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