Automatic evaluation of machine translation (MT) is based on the idea that the quality of the MT output is better if it is more similar to human translation (HT). Whereas automatic metrics based on this similarity idea enable fast and large-scale evaluation of MT progress and therefore are widely used, they have certain limitations. One is the fact that the automatic metrics are not able to recognise acceptable differences between MT and HT. The frequent cause of these differences are translation shifts, the optional departures from theoretical formal correspondence between source and target language units for the sake of adapting the text to the norms and conventions of the target language. This work is based on the author’s own translatio...
The emergence of Machine Translation, known as MT has given a new hope to abridge the problems in tr...
This work investigates the potential use of post-edited machine translation (MT) outputs as referenc...
Automatic evaluation measures such as BLEU (Papineni et al. (2002)) and NIST (Doddington (2002)) are...
Automatic evaluation of machine translation (MT) is based on the idea that the quality of the MT out...
This paper reports on an initial study that aims to understand whether the acceptability of transla...
Both manual and automatic methods for Machine Translation (MT) evaluation heavily rely on profession...
<p>As machine translation quality continues to improve, the idea of using MT to assist human transla...
Any scientific endeavour must be evaluated in order to assess its correctness. In many applied scien...
This paper studies the impact of machine translation (MT) on the translation workflow at the Directo...
We present the first ever results show-ing that tuning a machine translation sys-tem against a seman...
Evaluation of machine translation (MT) output is a challenging task. In most cases, there is no sing...
The effect of translationese has been studied in the field of machine translation (MT), mostly with ...
Title: Measures of Machine Translation Quality Author: Matouš Macháček Department: Institute of Form...
The recent improvements in neural MT (NMT) have driven a shift from statistical MT (SMT) to NMT, wh...
Evaluation of machine translation (MT) is a difficult task, both for humans, and using automatic met...
The emergence of Machine Translation, known as MT has given a new hope to abridge the problems in tr...
This work investigates the potential use of post-edited machine translation (MT) outputs as referenc...
Automatic evaluation measures such as BLEU (Papineni et al. (2002)) and NIST (Doddington (2002)) are...
Automatic evaluation of machine translation (MT) is based on the idea that the quality of the MT out...
This paper reports on an initial study that aims to understand whether the acceptability of transla...
Both manual and automatic methods for Machine Translation (MT) evaluation heavily rely on profession...
<p>As machine translation quality continues to improve, the idea of using MT to assist human transla...
Any scientific endeavour must be evaluated in order to assess its correctness. In many applied scien...
This paper studies the impact of machine translation (MT) on the translation workflow at the Directo...
We present the first ever results show-ing that tuning a machine translation sys-tem against a seman...
Evaluation of machine translation (MT) output is a challenging task. In most cases, there is no sing...
The effect of translationese has been studied in the field of machine translation (MT), mostly with ...
Title: Measures of Machine Translation Quality Author: Matouš Macháček Department: Institute of Form...
The recent improvements in neural MT (NMT) have driven a shift from statistical MT (SMT) to NMT, wh...
Evaluation of machine translation (MT) is a difficult task, both for humans, and using automatic met...
The emergence of Machine Translation, known as MT has given a new hope to abridge the problems in tr...
This work investigates the potential use of post-edited machine translation (MT) outputs as referenc...
Automatic evaluation measures such as BLEU (Papineni et al. (2002)) and NIST (Doddington (2002)) are...