A Constrained Viterbi Relaxation For Bidirectional Word Alignment
PROCEEDINGS OF THE 52ND ANNUAL MEETING OF THE ASSOCIATION FOR COMPUTATIONAL LINGUISTICS, VOL 1(2014)
摘要
Bidirectional models of word alignment are an appealing alternative to post-hoc combinations of directional word aligners. Unfortunately, most bidirectional formulations are NP-Hard to solve, and a previous attempt to use a relaxation-based decoder yielded few exact solutions (6%). We present a novel relaxation for decoding the bidirectional model of DeNero and Macherey (2011). The relaxation can be solved with a modified version of the Viterbi algorithm. To find optimal solutions on difficult instances, we alternate between incrementally adding constraints and applying optimality-preserving coarse-to-fine pruning. The algorithm finds provably exact solutions on 86% of sentence pairs and shows improvements over directional models.
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