期刊名称：Conference on European Chapter of the Association for Computational Linguistics (EACL)
出版年度：2017
卷号：2017
页码：625-630
语种：English
出版社：ACL Anthology
摘要：Many errors in phrase-based SMT can be attributed to problems on three linguistic levels: morphological complexity in the target language, structural differences and lexical choice. We explore combinations of linguistically motivated approaches to address these problems in English-to-German SMT and show that they are complementary to one another, but also that the popular verbal pre-ordering can cause problems on the morphological and lexical level. A discriminative classifier can overcome these problems, in particular when enriching standard lexical features with features geared towards verbal inflection.
