2017年3月
Constrained Partial Parsing Based Dependency Tree Projection for Tree-to-Tree Machine Translation
自然言語処理
- ,
- ,
- ,
- 巻
- 24
- 号
- 2
- 開始ページ
- 267
- 終了ページ
- 296
- 記述言語
- 英語
- 掲載種別
- 研究論文(学術雑誌)
- DOI
- 10.11185/imt.12.172
- 出版者・発行元
- Information and Media Technologies 編集運営会議
<p>Ideally, tree-to-tree machine translation (MT) that utilizes syntactic parse trees onboth source and target sides could preserve non-local structure, and thus generatefluent and accurate translations. In practice, however, firstly, high quality parsers forboth source and target languages are difficult to obtain; secondly, even if we havehigh quality parsers on both sides, they still can be non-isomorphic because of theannotation criterion difference between the two languages. The lack of isomorphismbetween the parse trees makes it difficult to extract translation rules. This extremelylimits the performance of tree-to-tree MT. In this article, we present an approachthat projects dependency parse trees from the language side that has a high qualityparser, to the side that has a low quality parser, to improve the isomorphism of theparse trees. We first project a part of the dependencies with high confidence to makea partial parse tree, and then complement the remaining dependencies with partialparsing constrained by the already projected dependencies. Experiments conductedon the Japanese-Chinese and English-Chinese language pairs show that our proposedmethod significantly improves the performance on both the two language pairs.</p>
- リンク情報
- ID情報
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- DOI : 10.11185/imt.12.172
- CiNii Articles ID : 130006078764