The CMU-UKA syntax augmented machine translation system for IWSLT-06
نویسندگان
چکیده
We present the CMU-UKA Syntax Augmented Machine Translation System that was used in the IWSLT-06 evaluation campaign. We participated in the C-Star data track using only the Full BTEC corpus, for Chinese-English translation, focusing on transcript translation. We applied techniques that produce true-cased, punctuated translations from non-punctuated Chinese transcripts, generating translations which score higher against the Official metric than against the lower-cased, punctuation removed metric. Our results demonstrate the impact of syntax and hierarchy based models for speech transcript translation.
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