The impact of post-editing and machine translation on creativity and reading experience

Abstract

This article presents the results of a study involving the translation of a fictional story from English into Catalan in three modalities: machine-translated (MT), post-edited (MTPE) and translated without aid (HT). Each translation was analysed to evaluate its creativity. Subsequently, a cohort of 88 Catalan participants read the story in a randomly assigned modality and completed a survey. The results show that HT presented a higher creativity score if compared to MTPE and MT. HT also ranked higher in narrative engagement, and translation reception, while MTPE ranked marginally higher in enjoyment. HT and MTPE show no statistically significant differences in any category, whereas MT does in all variables tested. We conclude that creativity is highest when professional translators intervene in the process, especially when working without any aid. We hypothesize that creativity in translation could be the factor that enhances reading engagement and the reception of translated literary texts.

Post-editese in Literary Translations

“…Further analysis in the different literary genres is necessary in order to answer our research question more comprehensively, and so, the question whether there are characteristics of PE literary texts that possibly make them less creative than HT texts remains open. Nevertheless, based on our results, we assume that literary creativity in PE texts may be compromised, as shown by the Guerberof-Arenas and Toral [1], due to the influence of the MT lexical and syntactic choices on the translators' choices. As seen, the MT output performs a translation that tends to be as equivalent as possible to their source texts.…”

“…The excerpt from the TGOTT, both the original in English and its human translation, is freely available online, from which 260 lines (5155 tokens) were selected. We chose the AW test set for two reasons: first, because it was the test set used in our previous work [22] and so it enables us to draw some correlations between the present study and this previous one; second, because it is a fantasy genre which contains metaphors, idioms and irony, thus its translation involves more creativity on the part of the translators and post-editors to adapt its rich language to target language [1]. In this text genre, not only the plot is important, but rather the author's individual use of language, i.e., the author's style.…”

“…One of the biggest challenges for machine translation (MT) currently is to handle creative texts, such as literature, marketing content, etc., as these text types tend to contain a large amount of non-literal language, such as sarcasm, metaphor, irony and ambiguous elements of language that are likely to result in a word-by-word translation, thus compromising the rendering of the source text in the target language [1]. However, with the advent of neural MT systems (NMT), researchers in the field of artificial intelligence have identified a window of opportunity to translate creative texts more efficiently {2,3], as NMT systems are reported to outperform their predecessor, statistical MT systems, because they are able to learn the similarity between words and consider the context of the entire sentence, rather than just n-grams {4].…”

“…While a number of studies have investigated whether post-editing the MT output for literature might help literary translators in terms of productivity [e.g., 5, 2,3], translators' perception of MT is that the system is less useful for creative texts [5] than for other text types. In accordance with this, one study attempting to quantify creativity in MT and postedited (PE) literary texts investigated whether the translation modes impact the reader experience [1]. The study has shown that human translation (HT) scores higher for creativity than PE translations, although for reading experiences related to emotional engagement and narrative presence, no statistically significant differences between HT, MT and PE have been found.…”

Post-Editese in Literary Translations

“…One of the biggest challenges for machine translation (MT) currently is to handle creative texts, such as literature, marketing content, etc., as these text types tend to contain a large amount of non-literal language, such as sarcasm, metaphor, irony, and ambiguous elements of language that are likely to result in a word-by-word translation, thus compromising the rendering of the source text in the target language [1]. However, with the advent of neural MT systems (NMT), researchers in the field of artificial intelligence have identified a window of opportunity to translate creative texts more efficiently [2,3], as NMT systems are reported to outperform their predecessor, statistical MT systems, because they are able to learn the similarity between words and consider the context of the entire sentence, rather than just n-grams [4].…”