Friend or Foe: Machine Translation Implementation in Literature

In her lecture, “The World as India,” Susan Sontag notes that “translation is the circulatory system of the world’s literatures.” The translation she refers to here is literary translation—that branch of translation so often revered as the highest among its lesser, commercial peers such as technical translation, legal translation, etc. José Saramago has a similar claim: “writers make national literature, while translators make universal literature.” 

Why is it that people venerate literary translation, and what marks it different from other, more lucrative forms of translation? For starters, literary translation has always been associated with a certain sense of deliberation and contemplation, akin to creative writing and its highbrow superiority over technical and commercial writing. While the last decade has seen creativity play a bigger role in commercial sectors (e.g. transcreation, localization), the prestige they enjoy comes nowhere close to what literary translation enjoys. 

But each day, the gap between literary translation and non-literary translation closes ever more slightly; a large part of it is due to machine translation. With the advent of MT technology, translation has been demoted from the echelons of professionalism to an everyday chore: everybody can translate with the help of Google Translate (or some other generic engine). Anyone can utilize machine translation to achieve better translation results than ever before.

In the fourth issue of Counterpoint, the official online publication of the European Council of Literary Translators’ Associations (CEATL), president Morten Visby remarks that the threat of machine translation is a real one. Although there still remains for literary translators a “strong public perception of our cultural value as literary creators” and hence publishers are still wary of utilizing machine translation to cut costs, Visby claims that “literary translators may find themselves in an even more precarious position than their current one.” Machine translation already proffers plausible, near-human translations of contemporary genre literature—romance, thriller, mystery—between closely related languages, such as the Nordic or Romance languages.

In the same issue, other literary translators argue the opposite. A main proponent of human infallibility in translation is James Hadley, assistant professor in literary translation at Trinity College Dublin, who points out several crucial differences between human and machine translation in literature. For one, machine translation as of now only performs well in a specific domain in which the machine was trained; a machine trained with technical corpora will give better technical translations than, say, cookbook translations. On the other hand, Hadley writes that “in literature, not only are the writing conventions substantially different from many technical texts, [but] these conventions differ substantially between authors, time periods, genres, and forms of literature.” In other words, machines are not yet nuanced or robust enough to differentiate between the multivarious domains present within literature, and as a result, cannot provide fitting translations for literature. 

Another difference is that machine translation still operates on the word- and sentence-level, incapable of contextualization and chapter- (or book-) level translation, meaning sentences are translated in isolation. “But for literature, where ideas, metaphors, allusions and images can be recalled sentences, paragraphs, or even chapters later,” says Hadley, “the machines have a long way to go before they will be able to approach the skills of a human literary translator.” 

That’s not to say machines have no place in literary translation. For Hadley, machines do offer some help to translators, such as giving human translators “key details about the source text at a glance, which will allow them to work as efficiently as possible.” As such, Hadley notes that “developers [are] working on tools specifically to help literary translators.” The machine is an aid to human translation, not a replacement or alternative. 

Other translators in this issue of Counterpoint have similar opinions on this matter. UCD lecturer in German Hans-Christian Oeser delves deeper into this issue, speaking of his experiences in both human translation and post-editing. Oeser participated in a 2018 experiment comparing post-editing and human translation, the source text being F. Scott Fitzgerald’s The Beautiful and Damned; after completing both types of translation, Oeser found that “[his] “textual voice” was somewhat diminished in [his] post-edited work compared to its stronger manifestation in [his] earlier machine-independent German version.” 

Oeser isn’t completely disillusioned by machine translation; he notes that “in terms of the time spent on post-editing, as opposed to translating from scratch, it could be argued that the overall effort is somewhat less time-consuming.” Plus, Oeser admits that there is a degree of comfort that comes with knowing that the work of translating has already been carried out to a certain extent. 

But like Hadley, Oeser is not easily convinced. “The machine has, as of yet, no proper sense of context, of wordplay, ambiguity, polysemy, and metaphor or of rhetorical devices such as alliteration and assonance,” he writes, “it frequently mistranslates, using inappropriate words and phrases, seemingly chosen at random from its vast lexicon.” Even worse is the machine’s inability to maintain awareness of “elegance, of beauty, of stylistic coherence (or indeed intended breach of style),” and thus is devoid of that characteristic “sound” that all translators write with. 

In the end, Oeser comes to the conclusion as Hadley: “I would propose that every literary translator out to have the possibility and the right to utilise every tool at their disposal,” including digital dictionaries, translation memory and terminology management software, and online translation programs “of every description.” Machines can’t yet replace us, but they can aid us. As for the malicious publishing practice of utilizing post-editing as a means to cut costs, Oeser is vehemently against it and attempts to proselytize his passion against such practices, saying “we will have to be the Luddites of the humanities!” 

This threat of widespread post-editing practices is already happening around the world; complete machine translation has yet to happen, but MT developments are already wresting control away from human translators via post-editing. An assistant professor of literary translation at the University of Vienna, Waltraud Kolb is worried about the future; she anticipates “increasing pressure from publishers to cut costs this way, even though post-editing may be as cognitively demanding and time-consuming as translation.”

Kolb has previously carried out research on the effectiveness of high-quality post-editing, and found that it is “not much faster [than normal human translation]… the post-editors changed 90% of the sentences [of the source text] – the main problems the machine had were cohesion, reference, idioms, polysemy.” But publishing houses are likely to pay post-editors much less, given that the brunt of the “original” translation has been accomplished by a machine. 

With increasing usage of post-editing comes subsequent problems: Kolb predicts that wider post-editing practices could signify a near future in which “language will eventually become more uniform.” There’s also a concern for a decrease in general quality of writing—as Oeser notes—as well as copyright issues, which is a prevalent concern across all fields of translation. 

Post-editing—and the subsequent erasure of the translator’s role—is something Lawrence Venuti would have feared. A prominent translator and theorist, Venuti is known for his 1995 book, The Translator’s Invisibility, in which he argues against domesticating translations: a practice which effaces the translator’s in an attempt to make the translation sound more fluent in the target language. According to Venuti, the translator plays an equally important part in the novel’s translation process as the author, so much so that one could argue that a translator’s work is an original work in itself. 

In the case of post-editing, translators are rendered invisible not by the fluency with which they carry over the writer’s original voice; rather, translators are effaced by the monotone, unimodal voice that is the translation engine. Of course, different engines might sound different, but none of them will be able to offer, anytime soon, a nuanced, varied voice like the ones professional literary translators write with. 

This isn’t exactly in the vein of Venuti’s writing, but the logic applies; the translator has always held a precarious position, subject to erasure, deemed inferior to the authorship that looms over the entire text. These are practices that we should actively be moving away from; post-editing seems to be a regression back to the dark ages of translation which, arguably, we are still going through. This post on Book Riot by writer and editor Leah Rachen von Essen reveals that many major writers outside of the Anglosphere hide or erase their translators’ names when publishing their English translations. These best-selling writers include: Elena Ferrante, Haruki Murakami, Stieg Larsson, Cornelia Funke, and Mieko Kawakami. 

In short, a major concern to be addressed with the tide of post-editing and machine translation is the translator’s voice and agency: how do these new pieces of technology aid the translator in their job, physically and status-wise? Who do these developments in MT help, and at what cost?