My robotic friend? – My (belated) foray into Machine Translation POst Editing (MTPE)

 

As I wrote a few weeks ago, I have made the strategic decision to focus on my competitive advantage – Hebrew to English legal translation. The practical significance of that decision is that I must maximize its potential. Thus, this last week I took on a project involving editing machine translation of an insurance contract. I had previously avoided such projects due to their idiot-savant nature. The project confirmed many of my concerns but, in contrast, demonstrated the advantages of working on machine translation. I discovered that they could indeed be satisfying, both financially and emotionally.

In explanation of the term, machine translation does not necessarily refer to AI engines such as ChatGPT and may include older methods such as Google Translate. The term machine translation designates the initial use of a digital linguistic tool that translates the source text by applying similar patterns in a database, whether vetted and closed or open, Internet-based. Machine translation has existed for several decades, initially through translation memories developed by translators, agencies and companies and expanding to more sophisticated ones based on neural networks. The European Community has developed one of the most specific and sophisticated ones based on previous translations of all EU laws into all of the languages of the community. The open machine translations, notably Google Translate and AI, use statistical probability to choose the most probable translation available on the Internet. The quality of machine translation varies depending on the algorithm, language combinations and sources.

The resulting translation generally resembles one produced by an idiot-savant, which requires neither pure translation nor pure editing. To explain, if a human produces a poor text, it is far more economical in time and energy to retranslate from scratch. Simply put, the editor does not trust anything the original translator did. On the other hand, an editor, identifying an excellent translation, trusts the resulting text in terms of content and merely makes tweaks to improve the language. Furthermore, the editor learns to find a pattern of these mistakes and focus on them. In any case, two pairs of eyes are always better than one, regardless of the skill level. By contrast, machine translation, in my limited experience, produces highly uneven and unpredictable results. One sentence can be perfect, even better than one the editor could write. The next one can be a complete disaster and require complete rewriting. Even more difficult, a given translation may appear correct but closer analysis shows small but significant errors. It requires careful attention to identify those issues. Thus, machine translation is not consistent in quality nor are its mistakes predictable.

In the text I did, the translation engine, DeepL, produced a mixed bag. On the one hand, there were very few content mistakes, i.e., a reader could correctly understand the meaning of the vast majority of the provisions, albeit with a bit of effort and a few terminology errors. On the other hand, it was clear that a human translator had not produced the text. Here is a partial list of the error types:

1.     Articles (he vs. it)

2.    Modals (misuse of “shall” to indicate future instead of legal obligation)

3.    Literal translation of phrases (has the right to instead of may)

4.    Inconsistent capitalization (company and Company)

5.    Translation of the name of the Company

6.    Keeping sentence in the passive (The premium will be paid… vs the Policyholder must pay……

7.    Misplaced adjective (the benefits retained vs the retained benefits)

Thus, the machine translation, while accurate, was not correct.

Upon completion of the project, I decided that I would take on more such projects. Granted, it required great attention, with many breaks, to catch the issues and improve the text. However, the original text was better in some ways than that produced by far too many human translators. Moreover, as I knew that no human was responsible for it, I did not get annoyed. Since I had priced the project by projected time after viewing the translation beforehand (which turned out to be fairly accurate) and offered two different quotes, light and heavy editing, the compensation was more than acceptable. Most importantly, the final text read well, always a satisfying result. Thus, I will now take on more such projects. Maybe robots could be our friends.

Translating instability

I have been a freelance translator for 15 years and have learned one thing about the business: it is dynamic. Specifically, the complex base through which translators ply their trade is in constant change, forcing us to try to understand and adjust to the best of our ability. These changes are reflected in four different areas, at least, that affect our livelihood for better or for worse.

Technology is a major cause of change. Computer-aided translation (CAT tools) utilities with their attendant term memories (TM) have been disputed and implemented for over a decade but have irrevocably changed the manner of translation and project management. Simply put, translator agencies in many cases expect translators to use these tools and accordingly produce more. While there are areas in which TM’s are much less practical, CAT tool use is now a norm.

More recently, neural translation (NT), a form of machine translation (not Google Translate), has shaken up the market. Without getting in the details of how it works, NT can produce understandable text from tens of thousands of pages at significantly less cost and time than human translation in certain cases. Depending on the area, the text may be far from Shakespeare but in many cases the reader will have no issue comprehending it. This automated translation is acquiring an ever-increasing market share and squeezing out certain translation sectors. On the other hand, it is creating a huge market for people to edit the NT output to make it readable. Given the fast pace of improvement of NT, it is hard to predict which niches will be available for translators in five years.

At the same time, the business structure of translation is rapidly changing due to agglomeration and public stock offering.  Once an industry based on small, local agencies, more and more large international business agencies are being created through purchases and mergers. To finance these moves, these large companies are going public, effectively transferring their ownership to the public. The impact of these two trends is to lower translation rates due to the reduction of competition and greater market knowledge of the large agencies on one hand and the need to produce profit to the shareholders on the other hand. To paraphrase Ralf Lemster, a leading German financial translator, we need to either master the technology to increase productivity or hone a specialty to attain high rates.  The middle ground is rapidly shrinking.

In the background of the transformations are local legal developments. For example, changes in patent law eliminated the need for translation of certain documents. By contrast, EU regulations have created a vast need for translation in previous small markets, such as Czech or Gaelic. Likewise, regional or national certification modifications ease or render difficult entry into these markets, affecting the rates. Various ISO and European standards have increased the need for proofreaders. The legal background is truly a wild card for a translator.

A slower but no less powerful force is the ebb and flow of a language itself. Translation into English is one of the few stable markets as few changes have occurred in the demand for documents in that language in the last decade. However, the use of some languages has increased due to economic development, such as Chinese and Korean, while others have declined, such as French. That said, regardless of how small the segment, the demand for transcreation, the localization of a source text into a seamless local version, is increasing and providing good rates for more creative translators of all minor languages.

To be clear, these changes are neither to the complete benefit or detriment of the translator. They both reduce and create opportunities. For example, while the market for translating contracts has definitely shrunk, the demand for editors and transcreators has increased exponentially. The challenge we face is to match our talents, both current and potential, to the opportunities at hand. This effort requires constant, active testing of the market to ascertain what the current situation is, not a simple task in the “fog of war” world of freelancing. “Plus ça change, plus ça reste la mēme chose” does not apply here because the only true constant in business (and life) is change even if we are unaware of the scope of its forces.