CimS - The CIS and IMS Joint Submission to WMT 2015 addressing morphological and syntactic differences in English to German SMT

Abstract

We present the CimS submissions to the WMT 2015 Shared Task for the translation direction English to German. Similar to our previous submissions, all of our systems are aware of the complex nominal morphology of German. In this paper, we combine source-side reordering and target-side compound processing with basic morphological processing in order to obtain improved translation results. We also report on morphological processing for English to French.

The LMU Munich Unsupervised Machine Translation Systems

“…Specifically, we participated in the unsupervised learning task which focuses on training MT models without access to any parallel data. The team has a strong track record at previous WMT shared tasks (Bojar et al, 2017(Bojar et al, , 2015(Bojar et al, , 2014(Bojar et al, , 2013 working on SMT systems (Cap et al, 2014(Cap et al, , 2015Weller et al, 2013;Peter et al, 2016; and proposed a top scoring linguistically informed neural machine translation system based on human evaluation at WMT17.…”

LMU Munich's Neural Machine Translation Systems for News Articles and Health Information Texts

“…Research on various different types of machine translation models has previously been conducted at LMU. Core SMT paradigms for LMU's past shared task participations include phrase-based models (Cap et al, 2015(Cap et al, , 2014bWeller et al, 2013;, hierarchical phrasebased models Peter et al, 2016), operation sequence models , and hybrids of statistical approaches with rule-based and deep syntactic components (Tamchyna et al, 2016b).…”