I am going to increase reordering diversity of n-best list generated by Moses in order to apply my reordering model (a re-ranker system) for improving translation quality.
In the first step due to low reordering diversity of the n-best list, i need that the n-best list is included by different sentences which have different reorderings.
For increasing the n-best list diversity, we generate 10000-best list and then select 100-best of sentences with different reorderings.
For generating 10000-best list we use stack diversity and cube-pruning options. There are two disadvantages:
1) This task is very time consuming because of generating 10000-best in the first step.
2) we loose lots of good translation candidates in terms of lexical choice. It is caused that our reranker system could not find better translation candidates in order to improve translation quality (BLEU score).
I am looking for new solution for increasing reordering diversity without aforementioned problems.
S.Farzi, Ph.D. Student
Natural Language Processing Lab,
School of Electrical and Computer Eng.,
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