Identifying the machine translation error types with the greatest impact on post-editing effort
Translation Environment Tools make translators' work easier by providing them with term
lists, translation memories and machine translation output. Ideally, such tools automatically …
lists, translation memories and machine translation output. Ideally, such tools automatically …
[PDF][PDF] Modelling annotator bias with multi-task gaussian processes: An application to machine translation quality estimation
Annotating linguistic data is often a complex, time consuming and expensive endeavour.
Even with strict annotation guidelines, human subjects often deviate in their analyses, each …
Even with strict annotation guidelines, human subjects often deviate in their analyses, each …
Post-editing machine translation: A usability test for professional translation settings
Traditionally, the quality of machine translation (MT) output at best was sufficient to serve as
an informative translation for users without any knowledge of the source language but not for …
an informative translation for users without any knowledge of the source language but not for …
Measuring difficulty in translation and post-editing: A review
Difficulty (or called mental load, cognitive effort) has been an importance topic in translation
and interpreting process research. This article first clarifies conceptual issues and reviews …
and interpreting process research. This article first clarifies conceptual issues and reviews …
Pre-editing and post-editing
This chapter describes pre-editing and post-editing concepts and processes derived from
the use of machine translation (MT) in professional and academic translation environments …
the use of machine translation (MT) in professional and academic translation environments …
A product and process analysis of post-editor corrections on neural, statistical and rule-based machine translation output
This paper presents a comparison of post-editing (PE) changes performed on English-to-
Finnish neural (NMT), rule-based (RBMT) and statistical machine translation (SMT) output …
Finnish neural (NMT), rule-based (RBMT) and statistical machine translation (SMT) output …
Perception vs. reality: measuring machine translation post-editing productivity
This paper presents a study of user-perceived vs real machine translation (MT) post-editing
effort and productivity gains, focusing on two bidirectional language pairs: English—German …
effort and productivity gains, focusing on two bidirectional language pairs: English—German …
Cognitive effort in translation, editing, and post‐editing
I Lacruz - The handbook of translation and cognition, 2017 - Wiley Online Library
The three‐way relationship between effort, speed, and quality makes it important for
translation process researchers to find ways to understand and measure the effort that …
translation process researchers to find ways to understand and measure the effort that …
Modeling subjective affect annotations with multi-task learning
In supervised learning, the generalization capabilities of trained models are based on the
available annotations. Usually, multiple annotators are asked to annotate the dataset …
available annotations. Usually, multiple annotators are asked to annotate the dataset …
Indices of cognitive effort in machine translation post-editing
Identifying indices of effort in post-editing of machine translation can have a number of
applications, including estimating machine translation quality and calculating post-editors' …
applications, including estimating machine translation quality and calculating post-editors' …