An efficient graph search decoder for phrase-based statistical machine translation
نویسندگان
چکیده
In this paper we describe an efficient implementation of a graph search algorithm for phrase-based statistical machine translation. Our goal was to create a decoder that could be used for both our research system and a real-time speechto-speech machine translation demonstration system. The search algorithm is based on a Viterbi graph search with an A* heuristic. We were able to increase the speed of our decoder substantially through the use of on-the-fly beam pruning and other algorithmic enhancements. The decoder supports a variety of reordering constraints as well as arbitrary ngram decoding. In addition, we have implemented disk based translation models and a messaging interface to communicate with other components for use in our real-time speech translation system.
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