This study presents empirical research on no-match, machine-translated and translation-memory segments, analyzed in terms of translators’ productivity, final quality and prior professional experience. The findings suggest that translators have higher productivity and quality when using machine-translated output than when translating on their own, and that the productivity and quality gained with machine translation are not significantly different from the values obtained when processing fuzzy matches from a translation memory in the 85-94 percent range. The translators’ prior experience impacts on the quality they deliver but not on their productivity. These quantitative findings are triangulatedwith qualitative data from an online question...
The recent improvements in neural MT (NMT) have driven a shift from statistical MT (SMT) to NMT, wh...
This paper presents a study of user-perceived vs real machine translation (MT) post-editing effort ...
This paper describes a pilot study undertaken to propose a model for the analysis of the respective ...
Machine-translated segments are increasingly included as fuzzy matches within the translation-memory...
This article presents results on the correlation between machine-translated and fuzzy matches segmen...
Machine-translated segments are increasingly included as fuzzy matches within the translation-memory...
Machine-translated segments are increasingly included as fuzzy matches within the translation-memory...
This article reports on a controlled study carried out to examine the possible benefits of editing M...
Machine translation (MT) quality is generally measured via automatic metrics, producing scores that ...
Using machine translation (MT) input represents a fundamental change in translators’ work mode. The ...
This paper studies the impact of machine translation (MT) on the translation workflow at the Directo...
As Machine Translation (MT) becomes increasingly ubiquitous, so does its use in professional transla...
In this chapter, we present results on the impact of professional experience on the task of post-edi...
The recent improvements in neural MT (NMT) have driven a shift from statistical MT (SMT) to NMT, wh...
This paper presents a study of user-perceived vs real machine translation (MT) post-editing effort ...
This paper describes a pilot study undertaken to propose a model for the analysis of the respective ...
Machine-translated segments are increasingly included as fuzzy matches within the translation-memory...
This article presents results on the correlation between machine-translated and fuzzy matches segmen...
Machine-translated segments are increasingly included as fuzzy matches within the translation-memory...
Machine-translated segments are increasingly included as fuzzy matches within the translation-memory...
This article reports on a controlled study carried out to examine the possible benefits of editing M...
Machine translation (MT) quality is generally measured via automatic metrics, producing scores that ...
Using machine translation (MT) input represents a fundamental change in translators’ work mode. The ...
This paper studies the impact of machine translation (MT) on the translation workflow at the Directo...
As Machine Translation (MT) becomes increasingly ubiquitous, so does its use in professional transla...
In this chapter, we present results on the impact of professional experience on the task of post-edi...
The recent improvements in neural MT (NMT) have driven a shift from statistical MT (SMT) to NMT, wh...
This paper presents a study of user-perceived vs real machine translation (MT) post-editing effort ...
This paper describes a pilot study undertaken to propose a model for the analysis of the respective ...