Professional-Quality Translation at Light Speed: Why Voice Recognition May Well be the Most Disruptive Translation Technology You’ve Never Heard of.

I’m sort of amazed translators working into English today still type out their translations on keyboards. Hunched over for endless hours at a time, day after day, banging away on an electronic version of a 19th century invention – a barely improved technology from Gutenberg’s movable type of the 15th century – all the while straining their fingers, eyes, wrists, back and weary souls.

It’s slow. It’s tedious. It’s exhausting.

It’s also why translator productivity keeps banging its head up against that relentlessly stubborn 2,000 – 3,000 words-per-day concrete ceiling.

 It’s about time to ask ourselves this: Why are we translators in the 21st century caught in a typing trap? Human speech is five to seven times faster; cognitive processing about ten to fifteen times faster. Our translating brains actually work closer to these speeds – something any simultaneous interpreter can tell you – not at the interminable slog rate imposed by the need to pound out individual letters one by one on a keyboard.

Voice-recognition: It almost seems like magic

Modern voice-recognition technology in English, on the other hand, has finally matured in speed and accuracy to the point where you can’t even talk faster than the computer can process your voice and turn it into text on the page. Believe me, I’ve tried. On several occasions recently I’ve attempted, just for fun, to outrun my English voice-recognition software (Dragon Naturally Speaking Professional Edition 11.5) by reading as fast as humanly possible from a finished text. I can’t do it. The computer always keeps up with me.

It’s blisteringly fast, it’s always available, it never gets tired, it’s scarily accurate and the translation quality is professional human quality.

OK, that last part is me. But still.

Voice recognition today enables professional-quality translation at light speed.

A Professional Translator’s Dream

Voice recognition is a professional translator’s dream. The translator simply “speaks” the translation out loud into a headset microphone and lets the computer handle transcription, control and navigation. So the translator is essentially recording a sight translation. Here are some of the many advantages of voice recognition in translation:

• Improved translation quality and stylistic voice. You can radically improve your ability to “stay in the moment” with the text in the conceptual cognitive process without any kind of physical distraction. Vocalizing the translation for me consistently improves the stylistic quality of the target English text because it adds my ear as an additional aural filter. Speaking the translation out loud also blocks source-language interference and inelegant constructions in my mind.

• You are freed from the time lag imposed by the keyboard. Even though I’m a reasonably accomplished touch typist (70 – 90 wpm) the physical act of typing and jumping back and forth with my eyes from source document to target computer screen – or even within text and dialog boxes on screen when using TM tools – has always been very costly to my thought process.

• You are no longer slave to the plodding, strenuous and unnecessary strains of typing. By that I mean not just fatigue and potential injury to fingers, wrists, neck and back in the long run, but the cost of physical exertion and posture distortion – and sitting for hours – every single work day. By contrast the only equipment I use in dictation is a very thin, lightweight digital headset that I sometimes forget I even have on.

• Voice recognition allows you to automate every interaction you have with your computer and still work with TM tools. So you can still use all the tricks and shortcuts and macros and TM tools you use now, and you can also edit and revise text, but now you just say them out loud instead of type them and the computer executes them for you automatically. 

• You can make a lot more money. Actually that’s a bit of an understatement. An accomplished dictating translator working in a very familiar field can produce 1,500 – 3,000 words per hour. Yes, you read that correctly. Per hour. It’s a draft translation (to be sure) and you will still need to revise it (always). But by using dictation you can increase your output – and your income – by around fourfold. This is one of the very many reasons that dictating translators very rarely complain about their incomes.

Caveats and Cautions

I’ve long proselytized on the virtues of dictation, dating all the way back to the Cretaceous Period of the 1980s when I began with an old cassette tape dictation machine and two full-time technical typists.

The first day I began dictating translations in the 1980s I almost couldn’t believe how much easier it was. I finished an 8-hour job in about an hour and a half and I just sat there, sort of stunned. I wasn’t quite sure what to do with the rest of my day.

In the late 1990s when I was running workshops and training seminars at ATA conferences, translators coined the term “Hendzel Unit” as a kind of shorthand to refer to my 10,000-word-per day production level by dictation in scientific and technical translation. So I’ve been at this for a long time.

It turned out that this approach came with some caveats, though.

• High-output dictation only works in fields and language pairs you know exceedingly well. I could dictate science and technology in a flash, but I’d worked hard to develop the subject-area expertise and translation skills in those areas. When I expanded into legal and financial translations later in the 1990s, for example, I was dismayed to find that I simply couldn’t dictate those texts. It took nearly five years before I had the subject expertise and familiarity to do it with ease.

Since dictation is a way to connect your mind to the page faster, your mind and voice need to be faster than your typing fingers are. If your mind does not work quickly enough in a given language direction or subject area, there will be no real benefit.

• You may need a bit of interpreter DNA nested into your genetic code to verbalize translations. Humans process spoken language and written language through different cognitive processes – even different pathways in the brain – so those areas need to be able to talk to one another. But most dictating translators I know are not working interpreters, so perhaps only a bit of that DNA is all that’s required.

• Professional-quality voice-recognition software must be available in your target language. This is a major stumbling block for some translators, as are the limits on the ability of English-language software to recognize certain forms of accented English. You can still hire typists to transcribe your dictation, but voice-recognition by definition is dependent on the availability of suitable software.

• Dictated translations are still drafts that require revision and editing. As you develop and refine your dictation skills you will reduce the volume of editing required, but it’s important to recognize that dictation is never a substitute for text revision and polishing.

• Higher-end computer hardware is required. Voice recognition software runs best on very fast processors with as much RAM as you can get – 16 GB is a great start – with a solid-state hard drive (ssd) ideal. This hardware configuration has only recently become reasonably affordable, but do expect to pay a bit more for hardware than is required for other applications.

The poor stepchild of translation technologies

Voice recognition has remained in the shadows as a translation technology principally because there’s nobody out there – beside the individual translators – who reap the enormous financial benefits from its use. In other words, there’s no immediate or ongoing financial benefit to anybody else along the translation food chain other than the translator.

By that I mean that in the TM and MT technology market, unfortunately, it seems that there’s always some non-translator with a hand in your pocket trying to sell you a platform or a tool or a technology where some of the ultimate cost benefit goes to your customer and not you. Not so with dictation.

Turn the per-word market to your advantage

Your mileage, as they say, may vary. But dictation is worth considering, especially when discussions of translator income seem unnecessarily focused on per-word or per-hour rates instead of on total output and productivity, especially in the case of dictation, where the productivity improvement remains 100% in the translator’s pocket.

So if the market insists that you be paid by the word, take advantage of that. Leverage technology and your own skills to deliver, on a regular basis, a dramatically larger volume of high-quality words.

Your bank account – and your weary fingers – will thank you for it.

Everybody Lies

Marketing claims  of universal expertise by freelance translators and “We Do Everything” agencies damage industry credibility and drive the commodity mentality

A handyman knocks on your front door.

“I can fix anything,” he announces when you answer.

“Well, my roof leaks,” you reply,” and I was thinking of getting some estimates —

“—I am the best at roofs!” he says, interrupting you. “Better than those roofing companies that rip you off.”

“OK, but sorry, I can’t talk right now,” you say, trying to be polite. “I need to take my daughter’s computer in to have it looked at and—“

“Computers! Yes! I can do that! I built a desktop from scratch once and everybody loves my computer work. Never had a complaint.”

At this point you stop, cross your arms and frown with suspicion.

“Can you surgically insert a catheter and stent into my carotid artery before noon?” you ask sarcastically.

“Of course! And at a great price!” he insists.

I’ve had this exact same conversation with freelance translator job applicants for well over 25 years. At the end of their frantic song-and-dance sales pitches, I feel as confident about their abilities as I do about the skills of the do-it-all handyman with the stratospheric overconfidence.

This is one of the many steep prices we pay for the zero-barrier-to-entry field of professional translation. Anybody can claim to be a “professional translator.” And a very large number of anybodies do.

Agency Offenders

Many translation agencies are even more guilty of these kinds of overreaching, handyman-class absurdities because they not only claim expertise in all subjects but also in “all languages,” a combination that is mathematically impossible. Expansive claims of language expertise on their websites list non-existent languages in text overrun with blatant grammatical errors and obvious misspellings as well as bizarre contradictions (“We are experts in transesophageal echocardiography….and we also do all subjects and languages!”)

Excruciating amateurishness

This kind of excruciating amateurishness severely undercuts our authority as language experts with customers and the public. And the commodity sector of the translation industry itself – beset with plunging chasms of insecurity and fretfulness driven by fears of ever-decreasing prices – desperately needs a professionalism makeover of the very highest order.

 

 

 10,000 Hours

It’s important to recognize above all that true mastery in language – and especially subject-matter expertise – requires brutal, hard work, measured in decades, and not the five minutes it takes to print “expert” on a business card. In fact, true world-class expertise and professionalism as a translator requires 10,000 hours of focused practice under skilled supervision with consistent expert feedback. 

Malcolm Gladwell’s 2008 book Outliers popularized this 10,000 hours figure, which in turn was based on human psychological and psychometric research originally conducted by Anders Ericsson. It dethroned a whole host of myths about expertise and talent:

“The striking thing about Ericsson’s study is that he and his colleagues couldn’t find any “naturals,” musicians who floated effortlessly to the top while practicing a fraction of the time their peers did. Nor could they find any “grinds,” people who worked harder than everybody else, yet just didn’t have what it takes to break the top ranks.

Their research suggests that once a musician has enough ability to get into a top music school, the thing that distinguishes one performer from another is how hard he or she works.

That’s it.

And what’s more, the people at the very top don’t just work harder or even much harder than everybody else. They work much, much harder.”

The neurologist Daniel Levitin has also found that 10,000 hours of practice is required to achieve the level of mastery associated with being a world-class expert – in anything. Whether it is concert pianists, ice skaters, chess players, fiction writers, or computer programmers – no one has yet found a case in which true world-class expertise was accomplished in less time.”

As Gladwell noted in his book, “Ten thousand hours is an enormous amount of time. It’s all but impossible to reach that number all by yourself by the time you’re a young adult.”

 

 Expertise in the Translation Industry

What first jumps out at language professionals from this research – aside from the refreshing scientific explanation of the universal absence of “young adult experts” anywhere in the language industry – is how convincingly it simultaneously dismantles the plague of claims of expertise based on “a natural talent for languages” or “long residence in foreign countries” or a “passion for things foreign” or “training in the most sophisticated Spanish in Latin America” (seriously?) and other specious silliness that pops up all over translators’ resumes. The point it drives home is this – there are no short-cuts, least of all those that are accidents of birth or circumstance or personal imagination.

And proximity to mastery – the expertise claimed on all those websites – requires that professional translators be very far along that 10,000-hour timeline.

Keys to success

Sadly, a significant number of working translators – not just beginners, but more than a few intermediate and even advanced ones, who have worked for longer than 10,000 hours, but alone and without editorial oversight, so they make the same mistakes over and over – have made the grave error of failing to develop true subject-matter expertise along that same 10,000-hour trajectory. Subject-matter expertise is not only the principal quality differentiator on the market, it’s the single best way to stand out from the competition. It opens the door to the high-end specialist and “value-added” language services companies as well as the direct client market.

So this failure is a terrible trap because translators without true subject expertise or editorial feedback are implicitly encouraged to maintain these appallingly bad habits by “We Do Everything” agencies that – contrary to what they tell their customers – do not edit or revise translators’ work, add value or provide feedback of any kind. It’s all about price. This is a toxic form of co-dependency that robs translators of their very ability to learn and improve.

Be careful what you ask for…..

An inevitable consequence of “We Do Everything” marketing so prevalent in the commodity sector of the translation industry is that it leads customers to the conclusion that “doing everything” is easy. It requires no special expertise because no special expertise is claimed by the providers. So translators and agencies in this sector are left to fight over market share for what they themselves portray as an indistinguishable product, which by definition makes it a commodity.

And the race to the bottom on price is underway.

 

 

Choosing markets

The one island of stability and sanity in the catastrophic cost-cutting, job-destroying, price-driven apocalypse of modern journalism is The Wall Street Journal.

The Wall Street Journal not only charges hundreds of dollars a year for their newspaper, they charge for access to their website.

The Wall Street Journal has always charged for access to its website.

There is a lesson here for the translation industry. Marketing to people with money who will pay for access to quality information – and where the cost of failure is extremely high – will always be a winning strategy. And even today this is true in the translation industry, where the high-end subject-matter-expert sector of the market continues to expand – and demand is strong – even as the pricing fistfights and free-falling rates are the prevailing reality below.

The Wall Street Journal does not “do everything.” But what they do, they do very, very well.

 

 

 

Three Lessons: Humility, Collaboration, Perseverance.

 All three – in that order – hold the key to becoming a world-class translator.

An interviewer, who was also a writer, once asked me how many words I’d translated before I published my first translated book for the American Institute of Physics. I imagined he expected an answer of perhaps ten thousand or so.

“About two million,” I replied.

Two million?! How is that possible?

“That’s a conservative figure, I think.”

I explained that I was young and had been dictating scientific translations from Russian into English for publication in scientific journals for almost a decade when I published my first book translation. I kept two technical typists busy full-time.

I might have added that I was also personally responsible for perhaps 1% of all US East Coast consumption of editorial red ink scrawled all over my translations.

It turned out that my translator-editor colleagues at the American Institute of Physics, Plenum Publishing, the Optical Society of America, the Congressional Research Service, the World Bank and the U.S. national labs, to name just a few, were even better than I was.

I thought of myself as a terrific translator at the time – don’t we all? I knew my subject-matter cold. I could write convincingly and clearly. I had completed tons of college coursework in translation at Georgetown and had published translations with nationally renowned Russian scholars at the Smithsonian. I’d been selected by scientific publishers from many hundreds of applicants, often the only translator chosen in a given selection round. The staff at the American Institute of Physics would always call me “Dr. Hendzel” when I called because many of the other translators on the translation program held PhDs in physics (I didn’t)  and they were wary of offending somebody (I would politely correct them, but they would just as politely ignore me.)

So this editorial brutalization took some getting used to.

Twice a week I’d receive these fat packets stuffed full of hard-copy final corrections (later I’d receive red-lined electronic files). It was feedback on a massive scale, constantly, every single year, across dozens of sub-disciplines in physics, optics and engineering, and seemingly without end.

It occurred to me that this level of collaboration and correction was a lot like the scientific enterprise itself.

You learn three things from this kind of decades-long editorial mauling.

1. Humility.

2. Collaboration.

3. Perseverance.

Welcome to the Commercial Translation Market

Fast forward a few years to when I jumped feet first into the commercial translation market with my company ASET.

The first of many sobering realizations you come to in the early phases of building a premier boutique translation company is that you cannot possibly do all the work yourself, even if you do dictate.

After seeking out and examining the actual translation work produced by your commercial colleagues, you soon begin to realize that something is terribly wrong.

The commercial translation market appears to be radically different from the scientific publication market in some very crucial ways.

Don’t get me wrong. Some of the work is genuinely good. This warms your heart and brings a smile to your weary face. But much of the technical, legal and even financial translations produced by some of the most visible and recognizable names in the commercial translation industry – even those with graduate translation degrees and certifications a mile long – are dramatically and bizarrely uneven.


This comes as a bit of a shock. How is this possible?

The quality spectrum and relative distribution looked something like this:

Publishable – Good – Understandable – Technical Fiction – Embarrassing – WTF?

After you’ve carefully evaluated several hundred translation samples yourself and had thousands more assessed by your former scientific-translator colleagues you do trust, a pattern begins to emerge.

The translators whose work is most solid – technically accurate, well-researched and elegantly written – are those who have had excellent technical subject-matter training (whatever relevant field) and have been translating professionally for a minimum of ten years. A decade appeared to be a tipping point.

But that’s only a start. Far more crucial to real expertise was the way these translators worked for all those years.

The Essential Role of Collaboration

The best translators had dodged the bullet of working in total isolation. They had spent their careers working in a massively collaborative environment – either physical or virtual (sometimes both). These people had been revised. They’d been edited. They’d been re-written. Their texts had been scrutinized, disemboweled, blasted apart and re-assembled.

They’d been fine-tuned and polished and burnished and shined.

Their translations had been at risk their entire careers: At risk for acceptance or rejection or revision by their own colleagues who were right there in the trenches working with them.

They would project their translations on screens at translation conferences and stand by them. They would reflect and consult and discuss with the session attendees ways to improve them.

Often conference interpreters who also worked as translators – the ultimate experts in collaboration and active learning from each other – were, surprisingly enough, much more flexible and receptive to instruction and guidance than were (written-only) translators with subject-matter training working into their native language of English.

Angry Isolationists

This rejection did not go over well with some of the translators whose work I evaluated, heavily edited and then rejected for requiring far too much intervention on every level.

“Your changes are a matter of opinion,” some sniffed (perhaps, but their translations were describing a physical world that did not actually exist).

“Here are my responses to your changes,” they would say, writing out 20-page single-spaced responses defending terms they “found in the dictionary” but made no sense in the context, to the extent that their context made any sense at all.

“Translators are creative artists and do their best work alone, like authors do,” some translators argued, often angrily and vociferously. It was pointed out to me more than once that Shakespeare worked alone (seriously). They would dispute the most minor of points and reject all feedback on principle. Most of these objections followed Sayre’s Law: “In any dispute, the intensity of the feelings is inversely proportional to the value of the issue at stake.”

“I’ve Never Had a Complaint from a Client.”

Then there were the translators who would defend their translation quality based on the specious and puzzling notion that they’d “never had a complaint from a client.”

This could not be true, first, because I was a client, and my rejection of their work based on a careful assessment was about as “complaint-y” as it gets.

Second, veterinarians never have complaints from their patients, either – nor do coroners – for perhaps the same reason that some translators don’t. Many clients cannot accurately assess translation quality – certainly monolingual clients can’t – so they say nothing at all.

Silence should not be confused with a vote of confidence.

The Exorbitant Price of Arrogance

All humans have an enormous cognitive and emotional investment in self-image. And translators are running a business, which supports their very livelihood. So these are some very sensitive grounds on which we tread.

Unfortunately, these translators had made the regrettable decision somewhere in their careers to defend their ego and self-image over all else, even (and especially) the quality of their product. This is a doomed strategy in a competitive market. It’s also an unfortunate one given the opportunities we all have to learn from colleagues through collaboration.

And even a modicum of modesty – or a realization of the limits the complexity of the world place on us – would have unwound all that defensive energy and pointed them into a much more productive – and ultimately happier – direction.

 

 

The Future has an Ancient Heart: Why Predictions about the Future of Language Technology Always Go Hopelessly Awry


“Scholars and scientists who work on mechanical translation believe that within a few years the system may greatly increase communication, particularly in technical subjects, by making translation quick, accurate and easy.”
The New York Times – January 8, 1954

Technology gurus of the future, writing in the 1950s, predicted that today’s world would be exploding in brilliant and flashy flying cars with huge fins, space suits, jet packs, shiny edible clothing, huge rocket ships, smart-aleck talking robots, house-sized computers and comfortable Moon colonies.

Instead, the cars shrank, the space suits disappeared, the house-sized computers now fit in your hand, the robots are faceless wired Legos and the Moon colonies were erased from the drawing board before they even began.

The real technology revolution turned out to be exactly the opposite of the predictions.

Things didn’t get larger, they got smaller. The technology was not flashy, it disappeared silently into unimaginably more powerful hand-held devices.

Electronics did not fill rooms, it slid into pockets.

And what about all those newspapers they were reading during breakfast on the ultra-modern Moon colonies?

Nope, no moon colonies.

Also, no newspapers.

And machine translation is still clunky and unreliable nearly 60 years after the New York Times prediction above.

An outcome that’s exactly the opposite of the prediction.

How could all these predictions have gone so impossibly awry?

Predictions of explosive technological change are almost always wrong. What futurists think of as their own “imagination” is really a mirror reflection of what’s already staring them in the face that very day (such as the US space program in the 1950s) suddenly applied to the entire world (We’ll all live in space!), which is an unfortunately stale and unimaginative practice of taking whatever exists and simply extending it randomly into the future by making it larger or faster or more colorful or otherwise “futuristic.”

“Translating machines will soon take their place beside gramophone records and colour reproduction in the first rank of modern techniques for the spread of culture and science.”
Emile Delavenay
December, 1958

Futurists are overly seduced by the newest technology, most of which fails or is discarded or becomes outdated in the near term (8-track tapes, black-and-white TV, AM radio, the DeLorean) making what seems “futuristic” at the time unlikely to survive into the real future.

Hopeful technocratic predictions are also overly reliant on the views and opinions of engineers, who tend to have a narrow solutions focus that is surely admirable in its efficiency and focus (it got us to the Moon), but a bit too spartan and utilitarian for people to embrace (“I’m not wearing aluminum!”)

And that brings us to the most important reason that technology predictions fail:

Successful technology is always shaped by human interaction: Technology that does not improve or advance or align with human experience will be modified, rejected or ignored.

The philosopher, quantitative analyst and former Wall Street trader Nassim Nicholas Taleb describes in his recently published book Antifragile how the technology that’s succeeded over long stretches of human history is likely to survive into the future – and triumph against challenges – strictly by virtue of its hard-earned symbiotic relationship with humans.

So consider what did not change today in the face of our 1950s wide-eyed futurists’ whiz-bang space predictions of new things to come in our daily lives like “shiny synthetic space suits and nutritionally optimized pills”:

“Tonight I will be meeting friends in a restaurant (tavernas have existed for at least twenty-five centuries). I will be walking there wearing shoes hardly different from those worn fifty-three hundred years ago by the mummified man discovered in a glacier in the Austrian Alps. At the restaurant, I will be using silverware, a Mesopotamian technology, which qualifies as a “killer application” given what it allows me to do to the leg of lamb, such as tear it apart while sparing my fingers from burns. I will be drinking wine, a liquid that has been in use for at least six millennia. The wine will be poured into glasses, an innovation claimed by my Lebanese compatriots to come from their Phoenician ancestors, and if you disagree about the source, we can say that glass objects have been sold by them as trinkets for at least twenty-nine hundred years. After the main course, I will have a somewhat younger technology, artisanal cheese, paying higher prices for those that have not changed in their preparation for several centuries.”

The point here is not that old technologies are always best – after all, I use voice-recognition technology in my own translations of physics on a hardware system I designed myself – it’s that technologies that old have survived an astronomically large number of destructive challenges over the centuries and yet have survived intact today – in fact, prospered from those challenges – because they are imperceptibly woven into the human experience.

Language Technology

Language is a special case in technology because it’s the most essentially human of all possible cognitive activities. That makes it very nearly organic in evolution and behavior, erratic and unpredictable, frustrating and counter-intuitive, and unusually resistant to successful algorithmic manipulation.

Recent research in cognitive psychology has consistently demonstrated that human intelligence in decision-making is at its core overwhelmingly emotional, often irrational, and exceedingly human-bias-driven. So that makes it a highly intuitive activity, a domain that has continued to frustrate researchers in artificial intelligence (AI) since its inception.

The obsession in AI with all things “logical” as the core concept in defining “intelligence” is a false artifact of a failed imagination – and a trap Hollywood has deftly avoided.

“I’m sorry, Dave. I’m afraid I can’t do that.” – HAL, 2001: A Space Odyssey (1968)

In MT, these constraints, among others, force persistent errors as the code scrambles to keep up with the sprinting language. This rampant error propagation in MT is also why post-editors are so crucial to every step of the machine translation enterprise.

Today’s post-editors function much like the mechanic who takes up permanent residence in the passenger seat of the forever failing two-seater Jaguar sports cars of the 1960s that would break down endlessly, assuming that they started at all.

Upgrade the code – problem solved

Improvements in technology have surely improved the quality of MT, which is why it has important and valuable applications in gisting, high-volume/low-quality translation and online on-the-fly translations — all areas where it will continue to expand and likely dominate.

The temptation to definitively solve the MT problem once and for all — to replace professional human translators –by “perfecting the technology,” however, much like re-engineering the Jaguar, fails on the nature of language itself.

Our own scientific study of language in linguistics reveals that ambiguity in language is a feature, not a flaw. It’s a recurring, inbuilt functionality that continually re-asserts itself and makes language a wonderful tool for describing a fuzzy world of ambiguity and inference and subtlety and nonlinear complexity and, of course, the downright messy realities of human relationships.

Including human relationships with technology.

The cost of failed predictions

You would think that this disastrous record of preposterously bad predictions would at least shame commentators into adopting a more modest or humble stance on language and technology, but hardly a week goes by today without yet another “Star Trek Universal Translator” article that comes to all the wrong conclusions.

This week The Economist set out to explain how the Universal Translator in Star Trek reads brain wave activity to accurately translate inter-galactic languages in the 23rd century. This is quite well-known in the science-fiction lore, and it was an unusually creative solution at the time because the Star Trek script writers were, uh, writers, who knew all the confounding rules responsible for the subtlety and power of language, which would certainly defeat any computer analysis they could reasonably foresee, even in the 23rd century.

But The Economist then promptly swung around and without even blushing – or hoping nobody noticed the card deck change – gave glowing reviews to a silicon-based, non-intuitive, non-contextual, non-brainwave-reading, early-21st century technology that is slavishly tied to individual words – a creaky, mistake-spewing Stone Age technology by comparison.

The future of coders

Perhaps what’s most striking in language technology predictions is the complete absence of even a hint of a prediction of the demise of computer programmers. After all, technological advancements in the modern motor vehicle have all but eliminated backyard screwdriver mechanics and tinkerers. Typewriter repairmen have been gone for decades. And nobody repairs computers today, anyway – it’s just faster and cheaper to buy new ones.  And how many new apps do you need when 1 million have already been written?

As technology improves, it becomes more transparent, reliable, and cheaper and dramatically less insistent on intervention.

Translators are the past – and the future

Translators should be the least concerned with advances in language technology. They have the one skill set that is essential to understanding and conveying meaning in human language.

That means that they are by far the most crucial link in the chain of viable MT.

The computer programmers, on the other hand, might want to think more carefully about their future, especially given the inverted way these technology predictions turn out. They may be tomorrow’s backyard screwdriver mechanics and tinkerers who suddenly find themselves out of work.

And can we put an end to the vaguely dismissive talking-down to translators from those failed technologists? I’m weary of watching the alchemists lecture us chemists – you know, the people who actually do all the valuable work, have done so for millennia, and will continue to do so in the future.

 

Translation is Not About Words. It’s About What the Words are About.

Subject-matter knowledge is not just “important” to translation.  It’s the very essence of translation.

Buried deep in the bedrock of every profession are certain truths that are universally understood and accepted by modern practitioners. In medicine, for example, those include a recognition that the human body exists in a physical universe subject to the laws of science and not to a fictitious universe of mysterious spirits accessible to the chosen, pre-ordained few, a concept that had dominated human medicine for millennia.

As a result, medical doctors strolling through a cocktail party today would never encounter questions from their friends, patients or colleagues about the effectiveness of specific spells, incantations or charms in their medical practice. Mysticism and superstition in medicine have been duly and effectively discarded in the proverbial dustbin of history.

Not so for translation.

We translators can spend decades of rigorous effort in the lead-up to our translation careers – and certainly during such careers – developing the crucial subject-matter expertise essential to the translation enterprise.

This process involves learning highly complex concepts in science, technology, philosophy, law, finance, business, music and dozens of other fields through immersion in the lab, lecture hall, classroom, production line, fabrication plant, trading floor or boardroom.

This prolonged effort is crucial to our ability to precisely convey all these concepts across language barriers.

But no matter how many fields we master as translators, awaiting us at that same cocktail party will be the eternal question that has been asked of translators since the Tower of Babel:

“How many languages do you speak?”

It’s a question that suggests an innocent, almost whimsical notion of translation as a low-stress career of light reflection, picked up effortlessly while flipping through phrase books and sipping sweet tea in the afternoon shade.

The reality is rather more sobering. In my case, for example, I’d arrive at such parties after having worked out certain issues in my translation work such as the principles underlying optical excitation of Rayleigh waves by interband light absorption or coherent acoustic resistance to an electron-hole plasma or approaches to calculating the electronic structure of alloys.

So my response to this friendly question of “how many languages do you speak?” would be a bit playful and would always be delivered with a smile:

“I speak science.”

Words or ideas?

It’s not the fault of our polite party-goer asking the “how many languages” question, since it’s just an attempt to strike up a friendly conversation.

And there’s no help from our culture, either – especially in the U.S. – where translators are looked upon with deep suspicion as these bizarre mythological creatures of ambiguous progeny whose field of endeavor is certainly trivial and should have been rendered mute by automated translation decades ago.

At the core of this fallacy is the ancient and somewhat quaint notion that translation is just about language – about words.

This can’t be true, though, because language itself isn’t even about words. The words of language are just the symbols we manipulate to paint meaning into our world — to project pictures that convey the underlying message, concept or idea.

So translators do not translate languages or words. They translate ideas.

And in today’s commercial translation market, that means we translate the ideas of people who are deeply invested in some highly complicated activities and are willing to pay us to convey them.


Since we must understand those ideas to do this accurately, we must know not only what we know, but we must also know what they know, too.

A solitary focus on language

What happens if a translator understands the languages, but not the ideas? How do those translations work out in the real world?

Short answer: Catastrophically.

The translation world today appears to be overflowing with novice (but certainly well-meaning) translators flailing about in dangerous waters infested with their own conceptual blindness. This is an inevitable outcome of the persistent and wrongheaded solitary focus on language to the exclusion of content.

It’s why students entering translation studies programs would be well advised to learn a great deal about the world before attempting to investigate ways to convey that knowledge – which is exactly what translation is – lest they end up conveying a disturbing and very costly lack of knowledge, an outcome that embarrasses both the novice translator and the poor unsuspecting client who, after all, thinks translation is just a matter of “speaking a foreign language.”

Russian has no words for that

One of my favorite stories that nicely illustrates this dilemma originated in an inquiry we once received from a U.S. manufacturer of a water purification system based on a novel yet straightforward technology that they wished to sell in Russia. The company had hired a translator – a Russian woman – to translate their technical documentation from English into Russian. They were getting nowhere with this approach and called me up to see if I could determine why.

“Every time we give her documentation to translate she says ‘Russian has no words for any of that,’” the manager told me. “Then she gets on the phone and speaks Russian all day with her friends. I don’t understand how she can speak that much Russian and not be able to translate what we need her to,” he said. “Is it true that Russian has no words for water purification?”

I assured him that Russian has a highly sophisticated technical lexicon, and in any event, it was unlikely that the language of Mendeleev – the author of the Periodic Table of Elements, after all – would prove utterly helpless in the face of reverse osmosis.

It was certainly possible that this woman was simply unaware of the technology (or was feigning ignorance of it), but in practice her apparent complete lack of any technical awareness was derailing the company’s efforts for reasons having nothing to do with language.

Line or link?

A more problematic case are translations that describe a world that doesn’t, can’t or will never exist.

And that happens because the translator doesn’t have the real-world knowledge to know what doesn’t, can’t or will never exist.

There are countless thousands of examples of this phenomenon. One is the word “liniya” in Russian, which means a physical telephone line such as a hard-wired copper landline. Unfortunately, the exact same Russian word also means a radio link to a remote terminal, satellite or cell tower, which is what cellphones use.

The only way to know which is correct is to possess the most rudimentary knowledge of telecommunications.

Alas, there never seems to be a limit to the English translations of this word that describe a world in which a physical copper wire is magically soldered to a satellite orbiting at an altitude of 42,000 kilometers.

Endless challenges

It’s certainly true that even the most experienced, careful and knowledgeable translators will find themselves in uncertain subject-matter territory at various points throughout their careers. It’s one of the many reasons to involve an expert colleague with greater subject-matter expertise in the review process while getting up to speed on technical concepts – a process that can and does take years.

Final appeal

In the event that I’ve failed to be convincing up to this point, consider again the title of this blog post:

Translation is not about words. It’s about what the words are about. 

The message here is that translation is about meaning, not about words. To illustrate this idea, I use the same words in both sentences. 

The only reason the meaning conveys is that the sentences are in different frames of reference. It’s the meaning underlying those frames of reference that delivers the idea.

 

 
 
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