This article introduces and evaluates several different word-level confidence measures for machine translation. These measures provide a method for labeling each word in an automatically generated translation as correct or incorrect. All approaches to confidence estimation presented here are based on word posterior probabilities. Different concepts of word posterior probabilities as well as dif...

RWTH participated in the shared translation task of the Fourth Workshop of Statistical Machine Translation (WMT 2009) with the German-English, French-English and Spanish-English pair in each translation direction. The submissions were generated using a phrase-based and a hierarchical statistical machine translation systems with appropriate morpho-syntactic enhancements. POS-based reorderings of...

Traditional simulation of a target architecture by interpreting object code can be improved by translating the object code to an intermediate format. This approach is called interpretive translation. Despite a substantial performance improvement over traditional interpretation, a large part of the overhead is unnecessary. An alternative approach is block translation, where one or more simulated...

The Dublin City University participated in the CLEF 2007 CL-SR English task. For CLEF 2007 we concentrated primarily on the issues of topic translation, combining this with search field combination and pseudo relevance feedback methods used for our CLEF 2006 submissions. Topics were translated into English using the Yahoo! BabelFish free online translation service combined with domain-specific ...

When we automatically acquire translation knowledge from a bilingual corpus, redundant rules are generated due to translation variety. To overcome this problem, we propose bilingual corpus cleaning based on translation literality. Word-level correspondence and phrase-level correspondence are applied as the criteria of literality. Using these criteria, a bilingual corpus was cleaned, and transla...

The Dublin City University participation in the CLEF 2007 CL-SR English task concentrated primarily on issues of topic translation. Our retrieval system used the BM25F model and pseudo relevance feedback. Topics were translated into English using the Yahoo! BabelFish free online service combined with domain-specific translation lexicons gathered automatically from Wikipedia. We explored alterna...

This paper presents the spoken language translation system developed at FBK-irst during the TC-STAR project. The system integrates automatic speech recognition with machine translation through the use of confusion networks, which permit to represent a huge number of transcription hypotheses generated by the speech recognizer. Confusion networks are efficiently decoded by a statistical machine t...

When we automatically acquire translation knowledge from a bilingual corpus, redundant rules are generated due to translation variety. To overcome this problem, we propose bilingual corpus cleaning based on translation literality. Word-level correspondence and phrase-level correspondence are applied as the criteria of literality. Using these criteria, a bilingual corpus was cleaned, and transla...

Interactive translation prediction (ITP) is a modality of computer-aided translation that assists professional translators by offering context-based computer-generated continuation suggestions as they type. While most state-of-the-art ITP systems follow a glass-box approach, meaning that they are tightly coupled to an adapted machine translation system, a black-box approach which does not need ...