Abstract

As the translation profession has become more technologized, translators increasingly work within an interface that combines translation from scratch, translation memory suggestions, machine translation post-editing, and terminological resources. This study analyses user activity data from one such interface, and measures temporal effort for English to Japanese translation at the segment level. Using previous studies of translation within the framework of relevance theory as a starting point, various features and edits were identified and annotated within the texts, in order to find whether there was a relationship between their prevalence and translation effort. Although this study is exploratory in nature, there was an expectation based on previous studies that procedurally encoded utterances would be associated with greater translation effort. This expectation was complicated by the choice of a language pair in which there has been little research applying relevance theory to translation, and by contemporary research that has made the distinction between procedural and conceptual encoding appear more fluid than previously believed. Our findings are that some features that lean more towards procedural encoding (such as prevalence of pronouns and manual addition of postpositions) are associated with increased temporal effort, although the small sample size makes it impossible to generalise. Segments translated with the aid of translation memory showed the least average temporal effort, and segments translated using machine translation appeared to require more effort than translation from scratch.

Highlights

  • In the years since the commercial introduction of translation memory (TM) tools circa 1992, specialised translation and localisation have become highly technologized

  • The source, target, and TM- suggested output analysis focused on the extent of the edits from TM/machine translation (MT) to target text based on these linguistic features

  • The average processing speed for the whole project was 0.28 words/second. This result compares favourably with previous research (Moorkens/O’Brien 2015) that contrasted expert and novice rates of productivity for English-German post-editing and found an average expert rate of 0.39 words/second, and average novice rate of 0.13 words/second

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Summary

Introduction

In the years since the commercial introduction of translation memory (TM) tools circa 1992, specialised translation and localisation have become highly technologized. In the previously mentioned research on translation effort, Alves/Gonçalves (2013) and Alves et al (2014) analysed translated texts in terms of the relevance theoretic distinction of procedural and conceptual encoding These are the two types of linguistic encoding that are acknowledged in relevance theory (Blakemore 1987, 2002, Wilson/Sperber 1993). The source, target, and TM- (or MT-) suggested output analysis focused on the extent of the edits from TM/MT to target text based on these linguistic features As this is an exploratory study, these features were annotated and enumerated without any prior hypothesis, based on research by Alves et al (2014), we expected to find a relationship between temporal effort and conceptual/procedural encoding, as we discuss in 3.2. Using common corpora analyses (such as the type/token ratio of lexical variation) in the WordSmith WordList tool, the mean segment length was 20.89 words, with a mean word length of 4.86 characters

Results
MT and TM suggestions
Discussionand Conclusion
Full Text
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