Word graphs for statistical machine translation
Abstract
Word graphs have various applications in the field of machine translation. Therefore it is
important for machine translation systems to produce compact word graphs of high quality.
We will describe the generation of word graphs for state of the art phrase-based statistical
machine translation. We will use these word graph to provide an analysis of the search
process. We will evaluate the quality of the word graphs using the well-known graph word
error rate. Additionally, we introduce the two novel graph-to-string criteria: the position-
independent graph word error rate and the graph BLEU score.
important for machine translation systems to produce compact word graphs of high quality.
We will describe the generation of word graphs for state of the art phrase-based statistical
machine translation. We will use these word graph to provide an analysis of the search
process. We will evaluate the quality of the word graphs using the well-known graph word
error rate. Additionally, we introduce the two novel graph-to-string criteria: the position-
independent graph word error rate and the graph BLEU score.
