|
This article is cited in 2 scientific papers (total in 2 papers)
On methods of machine translation quality assessment
A. K. Rychikhin Institute of Informatics Problems, Federal Research Center "Computer Science and Control" of the Russian Academy of Sciences, 44-2 Vavilov Str., Moscow 119133, Russian Federation
Abstract:
The article discusses approaches to determining the quality of machine
translation (MT) and several methods of translation quality assessment. The aim of
the article is to review a number of methods and approaches to human and
automatic assessment of MT quality. The first part of the article describes the
methods of relative human evaluation (ranking of translations) and absolute
evaluation based on penalties for errors in translation, as well as software and
algorithms that simplify human assessment. Most attention is paid to the
DQF/MQM
(Dynamic Quality Framework/Multidimensional Quality Metrics)
error typology which is not aimed at a limited subject area as the
most flexible one. The second part of the article is devoted to a review of metrics
for automatic quality assessment of MT that do not use linguistic data as well as
the correlation coefficients of human and automatic evaluation.
Keywords:
machine translation (MT), machine translation quality, rankings of translations and translation systems, MT quality metrics, error typologies, translation quality assessment, human evaluation of MT quality.
Received: 30.08.2019
Citation:
A. K. Rychikhin, “On methods of machine translation quality assessment”, Sistemy i Sredstva Inform., 29:4 (2019), 106–118
Linking options:
https://www.mathnet.ru/eng/ssi676 https://www.mathnet.ru/eng/ssi/v29/i4/p106
|
Statistics & downloads: |
Abstract page: | 687 | Full-text PDF : | 435 | References: | 34 |
|