학술논문

An Automatic Evaluation of the WMT22 General Machine Translation Task
Document Type
Working Paper
Source
Subject
Computer Science - Computation and Language
Language
Abstract
This report presents an automatic evaluation of the general machine translation task of the Seventh Conference on Machine Translation (WMT22). It evaluates a total of 185 systems for 21 translation directions including high-resource to low-resource language pairs and from closely related to distant languages. This large-scale automatic evaluation highlights some of the current limits of state-of-the-art machine translation systems. It also shows how automatic metrics, namely chrF, BLEU, and COMET, can complement themselves to mitigate their own limits in terms of interpretability and accuracy.
Comment: Update: correction, fr->de and de-> tables were switched