Add to ORKGDocument-level human evaluation of machine translation (MT) has been raising interest in the community. However, little is known about the issues of using document-level methodologies to assess MT quality. In this article, we compare the inter-annotator agreement (IAA) scores, the effort to assess the quality in different document-level methodologies, and the issue of misevaluation when sentences are evaluated out of context
In this chapter a survey is given of ways in which the output of machine translation can be evaluate...
Evaluation of machine translation (MT) is a difficult task, both for humans, and using automatic met...
Human-targeted metrics provide a compromise between human evaluation of machine translation, where h...
Document-level human evaluation of machine translation (MT) has been raising interest in the communi...
Recently, document-level (doc-level) human evaluation of machine translation (MT) has raised intere...
Document-level evaluation of machine translation has raised interest in the community especially sin...
MT-EQuAl (Machine Translation Errors, Quality, Alignment) is a toolkit for human assessment of Machi...
Title: Measures of Machine Translation Quality Author: Matouš Macháček Department: Institute of Form...
This work presents our efforts to reproduce the results of the human evaluation experiment presented...
This paper examines the motivation, design, and practical results of several types of human evaluati...
Machine translation evaluation is a very important activity in machine translation development. Auto...
Error analysis is a means to assess machine translation output in qualitative terms, which can be us...
We describe a focused effort to investigate the performance of phrase-based, human evaluation of mac...
In this paper we present a corpus-based method to evaluate the translation quality of machine transl...
Supervised approaches to NLP tasks rely on high-quality data annotations, which typically result fro...
In this chapter a survey is given of ways in which the output of machine translation can be evaluate...
Evaluation of machine translation (MT) is a difficult task, both for humans, and using automatic met...
Human-targeted metrics provide a compromise between human evaluation of machine translation, where h...
Document-level human evaluation of machine translation (MT) has been raising interest in the communi...
Recently, document-level (doc-level) human evaluation of machine translation (MT) has raised intere...
Document-level evaluation of machine translation has raised interest in the community especially sin...
MT-EQuAl (Machine Translation Errors, Quality, Alignment) is a toolkit for human assessment of Machi...
Title: Measures of Machine Translation Quality Author: Matouš Macháček Department: Institute of Form...
This work presents our efforts to reproduce the results of the human evaluation experiment presented...
This paper examines the motivation, design, and practical results of several types of human evaluati...
Machine translation evaluation is a very important activity in machine translation development. Auto...
Error analysis is a means to assess machine translation output in qualitative terms, which can be us...
We describe a focused effort to investigate the performance of phrase-based, human evaluation of mac...
In this paper we present a corpus-based method to evaluate the translation quality of machine transl...
Supervised approaches to NLP tasks rely on high-quality data annotations, which typically result fro...
In this chapter a survey is given of ways in which the output of machine translation can be evaluate...
Evaluation of machine translation (MT) is a difficult task, both for humans, and using automatic met...
Human-targeted metrics provide a compromise between human evaluation of machine translation, where h...