Discriminative Word Alignment by Linear Modeling
نویسندگان
چکیده
منابع مشابه
Discriminative Word Alignment by Linear Modeling
Word alignment plays an important role in many NLP tasks as it indicates the correspondence between words in a parallel text. Although widely used to align large bilingual corpora, generative models are hard to extend to incorporate arbitrary useful linguistic information. This article presents a discriminative framework for word alignment based on a linear model. Within this framework, all kno...
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For many years, statistical machine translation relied on generative models to provide bilingual word alignments. In 2005, several independent efforts showed that discriminative models could be used to enhance or replace the standard generative approach. Building on this work, we demonstrate substantial improvement in word-alignment accuracy, partly though improved training methods, but predomi...
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Bilingual word alignment forms the foundation of most approaches to statistical machine translation. Current word alignment methods are predominantly based on generative models. In this paper, we demonstrate a discriminative approach to training simple word alignment models that are comparable in accuracy to the more complex generative models normally used. These models have the the advantages ...
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ژورنال
عنوان ژورنال: Computational Linguistics
سال: 2010
ISSN: 0891-2017,1530-9312
DOI: 10.1162/coli_a_00001