In this paper, we describe compare-mt, a tool for holistic analysis and comparison of the
results of systems for language generation tasks such as machine translation. The main goal …

This chapter presents an overview of different approaches and tasks related to classification
and analysis of errors in machine translation (MT) output. Manual error classification is a …

With the rapid development of NLP research, leaderboards have emerged as one tool to
track the performance of various systems on various NLP tasks. They are effective in this …

Both lack of time and the need to translate texts for numerous reasons brought about an
increase in studying machine translation with a history spanning over 65 years. During the …

Machine translation can be considered a highly interdisciplinary and multidisciplinary field
because it is approached from the point of view of human translators, engineers, computer …

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 …

While recent changes in Machine Translation state-of-the-art brought translation quality a
step further, it is regularly acknowledged that the standard automatic metrics do not provide …

Error analysis is a means to assess machine translation output in qualitative terms, which
can be used as a basis for the generation of error profiles for different systems. As for other …

The present study aims to compare three systems: a generic statistical machine translation
(SMT), a generic neural machine translation (NMT) and a tailored-NMT system focusing on …

We introduce Addicter, a tool for Automatic Detection and DIsplay of Common Translation
ERrors. The tool allows to automatically identify and label translation errors and browse the …