Context-aware neural machine translation with mini-batch embedding

Makoto Morishita, Jun Suzuki, Tomoharu Iwata, Masaaki Nagata

研究成果: Conference contribution

抄録

It is crucial to provide an inter-sentence context in Neural Machine Translation (NMT) models for higher-quality translation. With the aim of using a simple approach to incorporate inter-sentence information, we propose mini-batch embedding (MBE) as a way to represent the features of sentences in a mini-batch. We construct a mini-batch by choosing sentences from the same document, and thus the MBE is expected to have contextual information across sentences. Here, we incorporate MBE in an NMT model, and our experiments show that the proposed method consistently outperforms the translation capabilities of strong baselines and improves writing style or terminology to fit the document's context.

本文言語English
ホスト出版物のタイトルEACL 2021 - 16th Conference of the European Chapter of the Association for Computational Linguistics, Proceedings of the Conference
出版社Association for Computational Linguistics (ACL)
ページ2513-2521
ページ数9
ISBN(電子版)9781954085022
出版ステータスPublished - 2021
イベント16th Conference of the European Chapter of the Associationfor Computational Linguistics, EACL 2021 - Virtual, Online
継続期間: 2021 4 192021 4 23

出版物シリーズ

名前EACL 2021 - 16th Conference of the European Chapter of the Association for Computational Linguistics, Proceedings of the Conference

Conference

Conference16th Conference of the European Chapter of the Associationfor Computational Linguistics, EACL 2021
CityVirtual, Online
Period21/4/1921/4/23

ASJC Scopus subject areas

  • ソフトウェア
  • 計算理論と計算数学
  • 言語学および言語

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