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Analysing the Impact of Interactive Machine Translation on Post-editing Effort

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Part of the book series: New Frontiers in Translation Studies ((NFTS))

Abstract

The combination of temporal, technical and cognitive effort has been proposed as metrics to evaluate the feasibility of post-editing on machine-translation (MT) output (Krings, 2001). In this study, we investigate the impact of interactive machine translation on the post-editing effort required to post-edit two specialized texts under experimental conditions and correlate it with Translation Edit Rate (TER) scores. Using the CasMaCat workbench as a post-editing tool in conjunction with a Tobii T60 eye tracker, process data were collected from 16 participants with some training on postediting. They were asked to carry out post-editing tasks under two different conditions: i) traditional post-editing (MT) and ii) interactive post-editing (IMT). In the IMT condition, as the user types, the MT system suggests alternative target translations which the post-editor can interactively accept or overwrite, whereas in the traditional MT condition no aids are provided to the user while editing the raw MT output. Temporal effort is measured by the total time spent to complete the task whereas technical effort is measured by the number of keystrokes and mouse events performed by each participant. In turn, cognitive effort is measured by fixation duration and the number of eye fixations (fixation count) in each task. Results show that IMT post-editing had significantly lower fixation duration and fewer fixation counts in comparison to traditional post-editing.

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Notes

  1. 1.

    CASMACAT: Cognitive Analysis and Statistical Methods for Advanced Computer Aided Translation was a project (2011–2014) co-funded by the European Union under the Seventh Framework Programme Project 287576 (ICT-2011.4.2).

  2. 2.

    http://opus.lingfil.uu.se/EMEA.php

  3. 3.

    Similar guidelines were also used in the other CASMACAT studies, including the EFT14 study (Chap. 3), the LS14 study (Chap. 5) and the CFT14 study (Chaps. 7 and 8).

  4. 4.

    Provided that this non-parametric test is computed with the median, such value is given for each condition (PE and ITP) as follows: PE = 901,637 and ITP = 1,199,500.

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Acknowledgements

The work described in this chapter was carried out within the framework of the EU project CASMACAT: Cognitive Analysis and Statistical Methods for Advanced Computer Aided Translation, funded by the European Union 7th Framework Programme Project 287576 (ICT-2011.4.2). Website: http://www.casmacat.eu. Brazilian researchers were funded by CNPq, the Brazilian Research Council (grant 307964/2011-6), and FAPEMIG, the Research Agency of the State of Minas Gerais (grant SHA/PPM-00170-14).

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Correspondence to Arlene Koglin .

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Alves, F. et al. (2016). Analysing the Impact of Interactive Machine Translation on Post-editing Effort. In: Carl, M., Bangalore, S., Schaeffer, M. (eds) New Directions in Empirical Translation Process Research. New Frontiers in Translation Studies. Springer, Cham. https://doi.org/10.1007/978-3-319-20358-4_4

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  • DOI: https://doi.org/10.1007/978-3-319-20358-4_4

  • Publisher Name: Springer, Cham

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