LLM translations of Peter Pan sit stylistically closer to human translations than NMT outputs do on several child-literature features, but the prompting strategy and possible training-data overlap partly explain the closeness.
Post-editese: an Exacerbated Translationese
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
abstract
Post-editing (PE) machine translation (MT) is widely used for dissemination because it leads to higher productivity than human translation from scratch (HT). In addition, PE translations are found to be of equal or better quality than HTs. However, most such studies measure quality solely as the number of errors. We conduct a set of computational analyses in which we compare PE against HT on three different datasets that cover five translation directions with measures that address different translation universals and laws of translation: simplification, normalisation and interference. We find out that PEs are simpler and more normalised and have a higher degree of interference from the source language than HTs.
fields
cs.CL 1years
2025 1verdicts
CONDITIONAL 1representative citing papers
citing papers explorer
-
Can Peter Pan Survive MT? A Stylometric Study of LLMs, NMTs, and HTs in Children's Literature Translation
LLM translations of Peter Pan sit stylistically closer to human translations than NMT outputs do on several child-literature features, but the prompting strategy and possible training-data overlap partly explain the closeness.