The Heidelberg University Machine Translation Systems for IWSLT 2013

We present our systems for the machine translation evaluation campaign of the International Workshop on Spoken Language Translation (IWSLT) 2013. We submitted systems for three language directions: German-to-English, Russianto-English and English-to-Russian. The focus of our approaches lies on effective usage of the in-domain parallel training data. Therefore, we use the training data to tune parameter weights for millions of sparse lexicalized features using efficient parallelized stochastic learning techniques. For German-to-English we incorporate syntax features. We combine all of our systems with large language models. For the systems involving Russian we also incorporate more data into building of the translation models.