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Cross-Language Comparability and Its Applications for MT

  • Bogdan BabychEmail author
  • Fangzhong Su
  • Anthony Hartley
  • Ahmet Aker
  • Monica Lestari Paramita
  • Paul Clough
  • Robert Gaizauskas
Chapter
Part of the Theory and Applications of Natural Language Processing book series (NLP)

Abstract

The concept of comparability, or linguistic relatedness, or closeness between textual units or corpora has many possible applications in computational linguistics. Consequently, the task of measuring comparability has increasingly become a core technological challenge in the field, and needs to be developed and evaluated systematically. Many practical applications require corpora with controlled levels of comparability, which are established by comparability metrics. From this perspective, it is important to understand the linguistic and technological mechanisms and implications of comparability and develop a systematic methodology for developing, evaluating and using comparability metrics. This chapter presents our approach to developing and using such metrics for machine translation (MT), especially for under-resourced languages. We address three core areas: (1) systematic meta-evaluation (or calibration) of the metrics on the basis of parallel corpora; (2) the development of feature-selection techniques for the metrics on the basis of aligned comparable texts, such as Wikipedia articles and (3) applying the developed metrics for the tasks of MT for under-resourced languages and measuring their effectiveness for corpora with unknown degrees of comparability. This has led to redefining the vague linguistic concept of comparability in terms of task-specific performance of the tools, which extract phrase-level translation equivalents from comparable texts.

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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Bogdan Babych
    • 1
    Email author
  • Fangzhong Su
    • 1
  • Anthony Hartley
    • 1
  • Ahmet Aker
    • 2
  • Monica Lestari Paramita
    • 2
  • Paul Clough
    • 2
  • Robert Gaizauskas
    • 2
  1. 1.University of LeedsLeedsUK
  2. 2.University of SheffieldSheffieldUK

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