2019 ACL ACL 2019

Linguistic Evaluation of German-English Machine Translation Using a Test Suite

Abstract

AbstractWe present the results of the application of a grammatical test suite for German-to-English MT on the systems submitted at WMT19, with a detailed analysis for 107 phenomena organized in 14 categories. The systems still translate wrong one out of four test items in average. Low performance is indicated for idioms, modals, pseudo-clefts, multi-word expressions and verb valency. When compared to last year, there has been a improvement of function words, non verbal agreement and punctuation. More detailed conclusions about particular systems and phenomena are also presented.

📈 Trend Setter — Syntax
🧭 Keyword Pioneer — test suite
🐝 Cross-Pollinator — Artificial Intelligence, Deep Learning, Machine Learning, Natural Language Processing, Speech & Audio
🌉 Interdisciplinary Bridge — Artificial Intelligence and Interdisciplinary and Machine Learning and Natural Language Processing