We present the PORTAGE statistical machine translation system which participated in the shared task of the ACL 2007 Second Workshop on Statistical Machine Translation. The focus of this description is on improvements which were incorporated into the system over the last year. These include adapted language models, phrase table pruning, an IBM1-based decoder feature, and rescoring with posterior...

Our approach to produce translations for the ACL-2016 Biomedical Translation Task on the English-Portuguese language pair, in both directions, is described. Own preliminary tests results and final results, measured by the shared task organizers, are also presented.

This paper presents a straightforward method to integrate co-reference information into phrase-based machine translation to address the problems of i) elided subjects and ii) morphological underspecification of pronouns when translating from pro-drop languages. We evaluate the method for the language pair SpanishEnglish and find that translation quality improves with the addition of co-referenc...

This paper addressees the problem of eliminating unsatisfactory outputs from machine translation (MT) systems. The authors intend to eliminate unsatisfactory MT outputs by using confidence measures. Confidence measures for MT outputs include the rank-sum-based confidence measure (RSCM) for statistical machine translation (SMT) systems. RSCM can be applied to non-SMT systems but does not always ...

Que hambre tengo yo What hunger have I Hungry I am so I am so hungry Have I that hunger ...

Article history: Received 24 August 2014 Received in revised form 9 December 2015 Accepted 14 December 2015 Available online 18 December 2015

We investigate how to improve bilingual embedding which has been successfully used as a feature in phrase-based statistical machine translation (SMT). Despite bilingual embedding’s success, the contextual information, which is of critical importance to translation quality, was ignored in previous work. To employ the contextual information, we propose a simple and memory-efficient model for lear...

This paper introduces three types of Statistical Machine Translation (SMT) output errors that would require grammatical knowledge for prevention. The first type is due to words that are negative in meaning but not in form. Problems arise when the negative forms are obligatory in target languages. The second type of errors is derived from the rigidity of pattern phrases or correlatives which do ...