The CUED HiFST System for the WMT10 Translation Shared Task
Juan Pino, Gonzalo Iglesias, Adrià de Gispert, Graeme Blackwood, Jamie Brunning, Bill Byrne · Cambridge University Engineering Department Publications Database · 2010
This paper describes the Cambridge University Engineering Department submission to the Fifth Workshop on Statistical Machine Translation. We report results for the French-English and Spanish-English shared translation tasks in both directions. The CUED system is based on HiFST, a hierarchical phrase-based decoder implemented using weighted finite-state transducers. In the French-English task, we investigate the use of context-dependent alignment models. We also show that lattice minimum Bayes-risk decoding is an effective framework for multi-source translation, leading to large gains in BLEU score.