Using Collocation Segmentation to Augment the Phrase Table
نویسندگان
چکیده
This paper describes the 2010 phrase-based statistical machine translation system developed at the TALP Research Center of the UPC in cooperation with BMIC and VMU. In phrase-based SMT, the phrase table is the main tool in translation. It is created extracting phrases from an aligned parallel corpus and then computing translation model scores with them. Performing a collocation segmentation over the source and target corpus before the alignment causes that di erent and larger phrases are extracted from the same original documents. We performed this segmentation and used the union of this phrase set with the phrase set extracted from the nonsegmented corpus to compute the phrase table. We present the con gurations considered and also report results obtained with internal and o cial test sets.
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