Category Archives: Deja Vu X

Talking to machines

Ever took a robocall? Pretty annoying, huh? A prerecorded message sounds on the other end of the line after a machine calls your phone number at dinnertime. The next morning, you need to call the DMV because you changed addresses. It is seldom a live human voice who answers the phone. We are all painfully familiar with the stock phrase offering us a language option: “Press 1 for English, press 2 for Spanish…»

AT&T and other companies save a lot of money by using IVRs (interactive voice response systems). A computer, not a human operator, interacts with a caller and responds/routes calls according to the nature of the query. Call centers fully operated by humans are costly to run. One way to reduce this cost is to outsource the customer service (or technical support) to a cheaper call center overseas. You or someone you know have already experienced this in the form of a support call for a company like Dell Computers taken overseas by a India-based call center. The guturally-accented English is noticeable. I have personally met some people at call centers in Córdoba, Argentina. Among their customers are cellphone companies. These employees have studied British English in college, which shows as a slight accent. This can be very annoying to a customer who is already irate about poor service.

In the genial movie Wargames, the term machine is mentioned by various characters in different situations, but the viewer gets the impression that there’s a question mark attached to the seemingly evident advantages given by our wondrous technologies. In the movie, a fully-automated computer system called WOPR (War Operation Plan Response) is in charge of controlling the launching of nuclear missiles, eliminating the need of human intervention. At one point, the WOPR detects (erroneously) that a Russian nuclear missile attack is under way. General Beringer, in charge of NORAD, asks Dr. McKittrick what the WOPR recommends, and the response is “Full-scale retaliatory strike.” Bemused and sarcastic, Gen. Beringer responds “I need some machine to tell me that?”

The WOPR system at NORAD in the movie Wargames

This could point to one of the morals of the story: Do we need a machine to tell us the obvious? Take some feature of your word processor, for example: if the spellchecker says it’s okay, it must be okay, right? And some automated features can become a hindrance to productivity and performance. I had a taste of this last week when I was readying a file to be exported back to Word format for a rush job. Because of some incomplete or corrupt codes, which I couldn’t immediately fix, the program repeatedly and consistently failed to export the file. It took me a few minutes of fiddling with the options until I fixed the problem, running against the clock.

Had I translated the document in plain wordprocessing fashion, with no CAT tool at hand, I would have not faced a corrupt code problem to begin with. But we translators also love technology, and the occasional hiccup is the price we pay for a more streamlined (irony intended) performance.

A few months ago, I ran into a more intractable problem. I was setting a Burmese translation in an InDesign CS3 document. Not knowing Burmese —a beautiful script, with elegant strokes and fanciful characters—, I first struggled with the correct font to display the characters correctly and then with the ligatures so that the words connected properly. Had I worked with a handwritten copy, I would have just erased the offending stroke, line or letter and rewrite. But a complex software like InDesign automates things like ligatures, kerning and other font features. It took me hours to get things right. Despite my technical knowledge, I still had to send a PDF copy in Burmese for approval by a human Burmese translator to make sure the script looked right, prior to final delivery.

You trust your dryer to do a proper job with your clothes but, would you trust a robot to paint your house? Surely you do online banking and do your taxes with the help of software, but, would you depend on artificial intelligence or ask a machine for financial advice? If you are single and looking, would you ask your friends to match you up with someone or would you trust online software in a dating site to match you up with someone? Would you carry on a love conversation with an Internet bot? Would you trust your company’s marketing tagline to a piece of software? Will you let software write up a sports column?

Actually, the latter scenario is already possible, thanks to Narrative Science‘s software. Last month, I spoke with Larry Adams, one of Narrative Science’s representatives, about the main features of their program, which mines data to author a piece of writing that is basically undistinguishable from what a human writer would create.

What if you need an email written in Mongolian translated into English in a rush? Enter Google Translate or any other number of software solutions, powered by machine translation. What drives the translation of large volumes of content, or bulk translation, is speed, not quality. Large companies that can afford the expense of custom-built machine translation software solutions already create multilingual versions of their technical documentation. Companies with a smaller wallet have to content themselves with us, human translators. For the sake of argument, I’ll oversimplify the issue a little bit. There are large translation companies that operate in bulk and outsource language services to the cheapest providers, from India to Argentina. Other companies try to stay competitive by emphasizing quality, then hire a more costly professional workforce in developed countries. The downward push on translation costs continue. After all, translation is usually viewed as a necessary cost of doing business, like buying office supplies or ordering printer ink cartridges.

While American business owners recognize the need and advantage of addressing the translation of documentation for their products or services, it is difficult for them to see the direct connection between higher sales and better-written translations. Hence, the advantages of quality translation are intangible ones, noble concepts in an abstract world. Companies with overseas offices trust their salespeople in the different geographies to check the accuracy of the translated documents. In-country reviews are an established quality control but translation managers often face an uphill battle to perform these reviews according to quality translation standards because the reviews’ completion depends on the time and availability of the reviewers —the people who are in charge of selling and marketing the products. Their main job is to market and sell, not to sit down and review translations, a task that is not a natural part of their role.

In the meantime, companies are offered a variety of technologies to automate most of the translation process: translation memories, terminology databases, automated quality controls, confirmed translations with lock-out of changes (so that future translators or editors cannot modify them once approved), and, of course, machine translation. As machine translation reaches new, more solid performance markers, a question insinuates itself: Will it be possible to completely automate the creative process of translation by sheer data mining and parsing of linguistic patterns in the corpus?

There is an intriguing article on self-driving cars in the latest issue of WIRED magazine. In the near future, it would be possible to let the driving to an advanced vehicle. Software solutions devised by companies like Narrative Science may make the high cost of writing standard sports news and financial articles a thing of the past, once the engine is properly customized. There seems to be a technological answer to our most pressing problems. Will translators be relegated to the mere role of editors, no more creators of original translations?

Machines and software, regardless of their level of automation, still operate in a GIGO fashion (garbage in, garbage out). The machine is no better than the operator that programmed it. Intuition, creativity, the right turn of phrase, the cumulative good judgment that comes from years of writing experience cannot be automated. Your business uses complex software and complex machines to churn out products and project sales. But, who do you turn to for sales, marketing or financial advice vital to your business? A machine? A software bot?

Towards the end of the movie Wargames, General Beringer faces a crisis. The highly sophisticated WOPR system warns of an impending Russian attack in the form of 2100 missiles, which may or may not be a simulation. The general is torn between ordering an attack for real and assuming that it’s a computer game gone awry, while the U.S. president is waiting for a decision on the phone. The creator of WOPR, Stephen Falken, reasons with him in this moment of terror:

-General, you are listening to a machine. Do the world a favor and don’t act like one.

Wise words to live by.

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Filed under Artificial Intelligence, Deja Vu X, Machine translation, QA standards, Trados

The elusive promise of productivity / La promesa escurridiza de la productividad

It happened again. I woke up at 4:30 a.m. (EST), my mind abuzz with ideas. So I got up and jotted them down because they seemed critical (read awesome) for an upcoming presentation at the ATA Conference in Boston. But the ideas kept coming.

I could stay in bed no longer; I decided to go for a short, brisk run (more like a trot, actually). It was 6:30 a.m. when I got out of my building’s door and out into the cool morning (57 ºF). I must have trotted for about 6 blocks when I started thinking on how important it is to move (my chiropractor keeps telling me that). We seldom make room for physical movement in our sedentary lives. As I was pondering this, cars zipped along to their routine destinations.

It dawned on me then: we use the wheel, the car, to move efficiently and quickly from point A to B, but the movement is unhealthy for our bodies. Why are we in a rush to move in that fashion? To get there earlier so that we have more time to…do what? To do nothing? I am as guilty as anyone else in this car culture in America.

But, what does this have anything to do with translation? Good answers come to those who wait: bear with me.

When I started my career in translation, my tool was the typewriter. The clickety-clack of keys was so comforting, it was music to my ears. I was probably doing 50-60 words per minute, but I spent more time reading, writing drafts, rewriting sentences and clauses, words and punctuation. Even in the heyday of CAT (computer-assisted translation) tools such as Trados Workbench and Transit in the mid 90s, I was still using what has become the equivalent of a typewriter: ah, the muffled clicking of a computer’s keyboard…still at 50-70 words per minute. I would spend a sometimes inordinate amount of time consulting dictionaries, magazines, and related books and websites to find the right expression…or a hint thereof at least.

I succumbed to the lure of the so-called productivity tools (CAT tools included) in late 1998 as a job requirement. I haven’t looked back since. The only typewriter I own is a portable Underwood model, about 80 years old, that I bought in 2007. It looks quaint in my curio cabinet, a reminder of more productive days of yesteryear. Sure, tools such as Trados and Deja Vu help me translate “faster.” But that’s an illusion. Nobody can write faster than they think, and not all of us think at the same rate.

Companies that sell CAT tools, SDLX in particular, promise us higher percentage rates of productivity as translators. But, is that necessarily a good thing, or even a healthy thing? What CAT tools really do is automate certain mechanical (and visible) tasks in translation, such as repeating already-translated texts and reusing partially or fully translated sentences and words. Nothing more. These tools do not make us better translators; it could be as well that they make us worse writers. Like the wheels of a car taking us fast and efficiently from point A to B, CAT tools take us from one language to another at increased speeds…leaving the road littered with misused words, typos, clunky expressions, awkward syntax, horrifying grammar. And those are not always accidents.

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Filed under Deja Vu X, Grammar, Productivity, TEnT tools, Tools, Trados, Translation as writing, Translation errors, Writing skills

No mousewheel scroll in TagEditor

So, what’s new? I have been using TagEditor since version 1.0 in 1998. Scrolling wheels in mice came much later. Yet, the developers of Trados and TagEditor didn’t bother to add the scrolling feature compatible with this new mouse. As a result, the translator or editor have to scroll content manually for pages on end with the help of the down arrow key. Very inefficient.

I recently wrote to the ideas.sdl.com site and posted an idea for an improvement: Add functionality for the mouse wheel in TagEditor. I receive the following response: Hi Mario, this all works in Studio, but we won’t be doing any more development of this nature in TagEditor. Sincerely Yours, The SDL Ideas Team

The upside: a personalized message, quick too (in less than 24 hours). The downside: the message is “use Studio 2009 instead of TagEditor.”

The fact is, I dislike SDL Studio 2009. Its cumbersome, dinosaur-sized interface is cluttered with windows and it is not very intuitive. To add insult to injury, SDL Studio 2009 only works with proprietary TM formats…unlike Trados or other products out there, that work in TXT and TMX formats.

So, a thumbs down on TagEditor, an otherwise fantastic tool for working with files in a wide variety of formats.

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Filed under Deja Vu X, SDL Studio 2009, TEnT tools, Tools, Trados