Human Post-editing in Hybrid Machine Translation Systems: Automatic and Manual Analysis and Evaluation

Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 745)


This study assesses, automatically and manually, the performance of two hybrid machine translation (HMT) systems, via a text corpus of questions in the Spanish and English languages. The results show that human evaluation metrics are more reliable when evaluating HMT performance. Further, there is evidence that MT can streamline the translation process for specific types of texts, such as questions; however, it does not yet rival the quality of human translations, to which post-editing is key in this process.


Hybrid machine translation Automatic evaluation Human evaluation Post-editing 



This work was supported by the University of Granada Special Research Programme - Starting Research Grants for Master Students.


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Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Department of Translation and Interpreting, Faculty of Translation and InterpretingUniversity of GranadaGranadaSpain
  2. 2.Department of Information and Communication, Colegio Máximo de CartujaUniversity of GranadaGranadaSpain
  3. 3.CSIC, Unidad Asociada Grupo SCImagoMadridSpain
  4. 4.University of GranadaGranadaSpain

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