Using noisy bilingual data for statistical machine translation

Stephan Vogel

doi:10.3115/1067737.1067777

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JOURNAL ARTICLE

Using noisy bilingual data for statistical machine translation

Stephan Vogel

Year: 2003 Vol: 2 Pages: 175-175

DOI: 10.3115/1067737.1067777

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Abstract

SMT systems rely on sufficient amount of parallel corpora to train the translation model. This paper investigates possibilities to use word-to-word and phrase-to-phrase translations extracted not only from clean parallel corpora but also from noisy comparable corpora. Translation results for a Chinese to English translation task are given.

Keywords:

Machine translation Computer science Phrase Natural language processing Artificial intelligence Translation (biology) Example-based machine translation Word (group theory) Task (project management) Parallel corpora Synchronous context-free grammar Transfer-based machine translation Machine translation software usability Rule-based machine translation Speech recognition Linguistics Engineering

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Topics

Natural Language Processing Techniques

Physical Sciences → Computer Science → Artificial Intelligence

Topic Modeling

Physical Sciences → Computer Science → Artificial Intelligence

Algorithms and Data Compression

Physical Sciences → Computer Science → Artificial Intelligence

Using noisy bilingual data for statistical machine translation

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