Add to ORKGThis paper presents the use of consensus among Machine Translation (MT) systems for the WMT14 Quality Estimation shared task. Consensus is explored here by com-paring the MT system output against sev-eral alternative machine translations using standard evaluation metrics. Figures ex-tracted from such metrics are used as fea-tures to complement baseline prediction models. The hypothesis is that knowing whether the translation of interest is simi-lar or dissimilar to translations from multi-ple different MT systems can provide use-ful information regarding the quality of such a translation.
We introduce referential translation machines (RTM) for quality estimation of translation outputs. R...
Machine Translation (MT) Quality Estimation (QE) aims to automatically measure the quality of MT sys...
This paper presents the results of the WMT09 shared tasks, which included a translation task, a syst...
Machine Translation Quality Estimation predicts quality scores for translations pro- duced by Machin...
This paper presents an empirical study on how different selections of input translation systems affe...
This paper presents the results of the WMT12 shared tasks, which included a translation task, a task...
Quality estimation evaluation commonly takes the form of measurement of the error that exists betwee...
In this paper, we address the problem of computing a consensus translation given the outputs from a ...
This paper presents the results of the WMT14 shared tasks, which included a standard news translatio...
In this paper, we address the problem of computing a consensus translation given the outputs from a ...
Most evaluation metrics for machine translation (MT) require reference translations for each sentenc...
Research on translation quality annotation and estimation usually makes use of standard language, so...
Machine Translation (MT) is being deployed for a range of use-cases by millions of people on a daily...
This paper describes the Universitat d’Alacant submissions (labelled as UAla-cant) for the machine t...
Research on translation quality annotation and estimation usually makes use of stan-dard language, s...
We introduce referential translation machines (RTM) for quality estimation of translation outputs. R...
Machine Translation (MT) Quality Estimation (QE) aims to automatically measure the quality of MT sys...
This paper presents the results of the WMT09 shared tasks, which included a translation task, a syst...
Machine Translation Quality Estimation predicts quality scores for translations pro- duced by Machin...
This paper presents an empirical study on how different selections of input translation systems affe...
This paper presents the results of the WMT12 shared tasks, which included a translation task, a task...
Quality estimation evaluation commonly takes the form of measurement of the error that exists betwee...
In this paper, we address the problem of computing a consensus translation given the outputs from a ...
This paper presents the results of the WMT14 shared tasks, which included a standard news translatio...
In this paper, we address the problem of computing a consensus translation given the outputs from a ...
Most evaluation metrics for machine translation (MT) require reference translations for each sentenc...
Research on translation quality annotation and estimation usually makes use of standard language, so...
Machine Translation (MT) is being deployed for a range of use-cases by millions of people on a daily...
This paper describes the Universitat d’Alacant submissions (labelled as UAla-cant) for the machine t...
Research on translation quality annotation and estimation usually makes use of stan-dard language, s...
We introduce referential translation machines (RTM) for quality estimation of translation outputs. R...
Machine Translation (MT) Quality Estimation (QE) aims to automatically measure the quality of MT sys...
This paper presents the results of the WMT09 shared tasks, which included a translation task, a syst...