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Part of
Translation in Transition: Human and machine intelligence
Edited by Isabel Lacruz
[American Translators Association Scholarly Monograph Series XX] 2023
► pp. 203–235

Chapter 10
Impact of word alignment on word translation entropy and other metrics

A comparison of translation process research findings derived from different word alignment methods

| Utah Valley University
| University of Málaga
| Kent State University
| Kent State University
Many of the findings from studies using the Center for Research and Innovation in Translation and Translation Technology (CRITT) Translation Process Research Database (TPR-DB) framework rely on word(s)-to-word(s) alignments of the source text and target text. However, little research has been done on the impacts different alignment methods have on these findings. This study compares two different manual word alignment methods and four automatic word alignment methods on the basis of one English-Spanish TPR-DB study that has been used extensively (the BML12 dataset). We replicate past findings from the BML12 dataset using these different alignments in order to determine the impact of alignment, and we present qualitative/quantitative analyses of the different word-alignment methods.
Keywords: word alignment, automatic word alignment, word translation entropy, replication study, CRITT TPR-DB
Article outline
  • 1.Introduction
  • 2.Summary of past research
  • 3.Procedure
    • 3.1Manual alignment
    • 3.2Automatic alignment
    • 3.3Post-processing
  • 4.Research questions 1 and 2: Qualitative analysis and replicating past studies
    • 4.1Carl and Schaeffer (2017)
    • 4.2Toledo-Báez and Carl (2020)
    • 4.3Ogawa et al. (2021)
  • 5.Research question 3: Comparing measures across the alignment methods
  • 6.Conclusions
    • 6.1RQ1: Is new manual alignment more consistent?
    • 6.2RQ2: Will alignment change results?
    • 6.3RQ3: Alignment consistency
    • 6.4Final remarks
  • Notes
  • References
  • Appendix
Published online: 26 July 2023
DOI logo
https://doi.org/10.1075/ata.xx.10gil
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Cited by (1)

Cited by one other publication

Carl, Michael
2024. An Active Inference Agent for Modeling Human Translation Processes. Entropy 26:8 ► pp. 616 ff. DOI logo

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