Word Association Models and Search Strategies for Discriminative Word Alignment
نویسندگان
چکیده
This paper deals with core aspects of discriminative word alignment systems, namely basic word association models as well as search strategies. We compare various low-computational-cost word association models: χ score, log-likelihood ratio and IBM model 1. We also compare three beam-search strategies. We show that it is more flexible and accurate to let links to the same word compete together, than introducing them sequentially in the alignment hypotheses, which is the strategy followed in several systems.
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