The UKA/CMU Statistical Machine Translation System for IWSLT 2006
Sanjika Hewavitharana, Bing Zhao, Almut Silja Hildebrand, Matthias Eck, Chiori Hori, Stephan Vogel, Alex Waibel · IWSLT · 2005
In this paper we describe the CMU statistical machine translation system used in the IWSLT 2005 evaluation campaign. This system is based on phrase-to-phrase translations extracted from a bilingual corpus. We experimented with two different phrase extraction methods; PESA on-the-fly phrase extraction and alignment free extraction method. The translation model, language model and other features were combined in a log-linear model during decoding. We present our experiments on model adaptation for new data in a different domain, as well as combining different translation hypotheses to obtain better translations. We participated in the supplied data track for manual transcriptions in the translation directions: ArabicEnglish, Chinese-English, Japanese-English and KoreanEnglish. For Chinese-English direction we also worked on ASR output of the supplied data, and with additional data in unrestricted and C-STAR tracks.