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Chapter 4. Post-editing neural machine translation in specialised languages

The role of corpora in the translation of phraseological structures
  • Natalie Kübler , Hanna Martikainen , Alexandra Mestivier and Mojca Pecman
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Recent Advances in Multiword Units in Machine Translation and Translation Technology
This chapter is in the book Recent Advances in Multiword Units in Machine Translation and Translation Technology

Abstract

This study focuses on phraseology in specialised texts and on students’ difficulties pertaining to phraseology in post-editing neural machine translation output. It is undertaken within the corpus-based methodological framework that we have developed for several purposes, one of which being to assess the impact of corpus use on translation and post-editing. The objective of the study is to propose a descriptive analysis of typical student errors related to phraseology in order to design tailored pedagogical materials. We aim to show that, with consistent training in querying corpora and in interpreting results in an appropriate manner, students can manage to improve their productions when translating specialised texts or when post-editing machine translation output.

Abstract

This study focuses on phraseology in specialised texts and on students’ difficulties pertaining to phraseology in post-editing neural machine translation output. It is undertaken within the corpus-based methodological framework that we have developed for several purposes, one of which being to assess the impact of corpus use on translation and post-editing. The objective of the study is to propose a descriptive analysis of typical student errors related to phraseology in order to design tailored pedagogical materials. We aim to show that, with consistent training in querying corpora and in interpreting results in an appropriate manner, students can manage to improve their productions when translating specialised texts or when post-editing machine translation output.

Chapters in this book

  1. Prelim pages i
  2. Table of contents v
  3. Preface vii
  4. Section 1. Computational treatment of multiword units
  5. Chapter 1. Multi-word units in neural machine translation 2
  6. Chapter 2. ReGap 18
  7. Chapter 3. Evaluating the Italian-English machine translation quality of MWUs in the domain of archaeology 40
  8. Chapter 4. Post-editing neural machine translation in specialised languages 57
  9. Chapter 5. Evaluating a bracketing protocol for multiword terms 79
  10. Section 2. Corpus-based and linguistic studies in phraseology
  11. Chapter 6. Suggestions for a new model of functional phraseme categorization for applied purposes 104
  12. Chapter 7. Verb collocations and their semantics in the specialized language of science 124
  13. Chapter 8. Negative–positive adjective pairing in travel journalism in English, Italian, and Polish 141
  14. Chapter 9. The middle construction and some machine translation issues 156
  15. Chapter 10. Semantic annotation of named rivers and its application for the prediction of multiword-term bracketing 173
  16. Chapter 11. Irony in American-English tweets 197
  17. Chapter 12. A comprehensive Japanese MWE lexicon 218
  18. Chapter 13. Ontology-based formalisation of Italian clitic verbal MWEs 243
  19. Index 263
https://doi.org/10.1075/cilt.366.04kub

Chapters in this book

  1. Prelim pages i
  2. Table of contents v
  3. Preface vii
  4. Section 1. Computational treatment of multiword units
  5. Chapter 1. Multi-word units in neural machine translation 2
  6. Chapter 2. ReGap 18
  7. Chapter 3. Evaluating the Italian-English machine translation quality of MWUs in the domain of archaeology 40
  8. Chapter 4. Post-editing neural machine translation in specialised languages 57
  9. Chapter 5. Evaluating a bracketing protocol for multiword terms 79
  10. Section 2. Corpus-based and linguistic studies in phraseology
  11. Chapter 6. Suggestions for a new model of functional phraseme categorization for applied purposes 104
  12. Chapter 7. Verb collocations and their semantics in the specialized language of science 124
  13. Chapter 8. Negative–positive adjective pairing in travel journalism in English, Italian, and Polish 141
  14. Chapter 9. The middle construction and some machine translation issues 156
  15. Chapter 10. Semantic annotation of named rivers and its application for the prediction of multiword-term bracketing 173
  16. Chapter 11. Irony in American-English tweets 197
  17. Chapter 12. A comprehensive Japanese MWE lexicon 218
  18. Chapter 13. Ontology-based formalisation of Italian clitic verbal MWEs 243
  19. Index 263
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