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.
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Trend Setter
— Syntax
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Keyword Pioneer
— test suite
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Cross-Pollinator
— Artificial Intelligence, Deep Learning, Machine Learning, Natural Language Processing, Speech & Audio
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Interdisciplinary Bridge
— Artificial Intelligence and Interdisciplinary and Machine Learning and Natural Language Processing
Topics
Natural Language Processing > Understanding > Semantic Analysis
Natural Language Processing > Understanding > Syntax
Natural Language Processing > Applications > Machine Translation
Interdisciplinary > Linguistics
Machine Learning > Optimization & Theory > Evaluation
Artificial Intelligence > Core AI > Natural Language Processing