Translator2Vec: Understanding and Representing Human Post-Editors
The combination of machines and humans for translation is effective, with many studies showing productivity gains when humans post-edit machine-translated output instead of translating from scratch. To take full advantage of this combination, we need a fine-grained understanding of how human translators work, and which post-editing styles are more effective than others. In this paper, we release and analyze a new dataset with document-level post-editing action sequences, including edit operations from keystrokes, mouse actions, and waiting times. Our dataset comprises 66,268 full document sessions post-edited by 332 humans, the largest of the kind released to date. We show that action sequences are informative enough to identify post-editors accurately, compared to baselines that only look at the initial and final text. We build on this to learn and visualize continuous representations of post-editors, and we show that these representations improve the downstream task of predicting post-editing time.
Code (1)
Tasks
TranslationSimilar Papers 제목 키워드 기반
Translator2Vec: Understanding and Representing Human Post-Editors
InDeep × NMT: Empowering Human Translators via Interpretable Neural Machine Translation
Neural machine translation (NMT) systems are nowadays essential components of professional translation workflows. Consequently, human translators are increasingly working as post-editors for machine-translated content. T…
Machine TranslationNMTTranslationIncremental Adaptation of NMT for Professional Post-editors: A User Study
A common use of machine translation in the industry is providing initial translation hypotheses, which are later supervised and post-edited by a human expert. During this revision process, new bilingual data are continuo…
Machine TranslationNMTTranslationMachine Translation and Post-Editing: Comparative Evaluation of Different MT Systems and Post-Editor Groups in Specialised Translation
This article aims to evaluate the quality of machine translation (MT) and post-editing (PE) in the context of specialised translation from English into French. Three MT systems (DeepL, eTranslation and Systran) were comp…
Machine TranslationLearning Non-Monotonic Automatic Post-Editing of Translations from Human Orderings
Recent research in neural machine translation has explored flexible generation orders, as an alternative to left-to-right generation. However, training non-monotonic models brings a new complication: how to search for a …
Automatic Post-EditingMachine TranslationTranslation