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The UKA/CMU statistical machine translation system for

By Matthias Eck, Ian Lane, Nguyen Bach, Sanjika Hewavitharana, Muntsin Kolss, Bing Zhao, Almut Silja Hildebr, Stephan Vogel and Alex Waibel


This paper describes the UKA/CMU statistical machine translation system used in the IWSLT 2006 evaluation campaign. The system is based on phrase-to-phrase translations extracted from a bilingual corpus. We compare two different phrase alignment techniques both based on word alignment probabilities. The system was used for all language pairs and data conditions in the evaluation campaign translating both the ASR output (as 1best) and the correct recognition results. 1

Year: 2013
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