Unsupervised Word Alignment by Agreement Under ITG Constraint
نویسندگان
چکیده
منابع مشابه
Unsupervised Word Alignment by Agreement Under ITG Constraint
We propose a novel unsupervised word alignment method that uses a constraint based on Inversion Transduction Grammar (ITG) parse trees to jointly unify two directional models. Previous agreement methods are not helpful for locating alignments with long distances because they do not use any syntactic structures. In contrast, the proposed method symmetrizes alignments in consideration of their st...
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3 Department of Computer Science, School of Computing, National University of Singapore Abstract. Inversion transduction grammar (ITG) [1] is an effective constraint to word alignment search space. However, the traditional unsupervised ITG word alignment model is incapable of utilizing rich features. In this paper, we propose a novel feature-based unsupervised ITG word alignment model. With the...
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Generative word alignment models, such as IBM Models, are restricted to oneto-many alignment, and cannot explicitly represent many-to-many relationships in a bilingual text. The problem is partially solved either by introducing heuristics or by agreement constraints such that two directional word alignments agree with each other. In this paper, we focus on the posterior regularization framework...
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Inversion transduction grammar (ITG) provides a syntactically motivated solution to modeling the distortion of words between two languages. Although the Viterbi ITG alignments can be found in polynomial time using a bilingual parsing algorithm, the computational complexity is still too high to handle real-world data, especially for long sentences. Alternatively, we propose a simple and effectiv...
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Word alignment has an exponentially large search space, which often makes exact inference infeasible. Recent studies have shown that inversion transduction grammars are reasonable constraints for word alignment, and that the constrained space could be efficiently searched using synchronous parsing algorithms. However, spurious ambiguity may occur in synchronous parsing and cause problems in bot...
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ژورنال
عنوان ژورنال: Journal of Information Processing
سال: 2017
ISSN: 1882-6652
DOI: 10.2197/ipsjjip.25.831