Flipbook Link: https://heyzine.com/flip-book/295aedfedf.html

How did the idea come up?

One of the participating interpreters Sasha commented: The thought of coming up with such a book is already an achievement.

That’s right, the idea to give advice to future interpreters didn’t occur to us until after having completed a series we did that compared professional interpreters to AI.

Starting from Interpreters and Music to Interpreters and Voices (https://www.youtube.com/playlist?list=PLO-QGEbwcTr2MdhbLPPGszMw8Rdc5J9aI), the 12 videos we’ve made in 6 months led us to a certain question:

• How are we going to pass the torch on to the future interpreters in the era of AI?”
• We began thinking about if it was possible for us to share advice to encourage the future of our industry.

Who did we reach out to?

This subject is bigger than our company (Monterey Language Services), so we reached out across the globe to various colleagues in the field to ask them what kind of advice they would give to future generations.

Judging by the number of quality, in-depth, and complete responses we received, it seems that our idea to seek out advice from colleagues was a step in the right direction.

Navigating the complex undertaking

Martha graciously shared the medal she was awarded for writing the bilingual publication. It was very inspirational and taught us that we can learn to open our mind beyond interpretation assignments! It awakened our awareness of our role and responsibilityto disseminate the value of our heritage to other language speakers.

As a result, we decided to pursue putting a face to their quotes and deliver even more layers of information to the project, and that thought has really elevated the project and made everything more intriguing!

Captions and pictures

We are totally in awe to receive amazing one-line captions, such as:

• Bing’s regarding “the wealth of information disguised as language”
• Lenne’s regarding eye contact on the job. Lenne brought it to our attention that there are many different theories as to how long to maintain eye contact and where to look while talking to someone vs. What an eye-opening piece of feedback from Lenne!
• When we received Elizabeth’s picture with lots of beautiful divine light on her face, we were blown away. She explained that her husband took that picture as she was preparing for prayer ministry at a Christian retreat.
• Elizabeth gave us 3 options for captioning. We picked one, but her other two are equally powerful:
• A peaceful heart helps our minds connect the right words. Don’t be overwhelmed; rely on help from above.
• The key to quick recall of obscure terminology is the peaceful alertness of a watchman.

Our director of translation, Mei-Ling, cannot agree more with Elizabeth that feeling peaceful is the way to cope with uncertainty or obscure situations that we often face at work. It’s at those times that we should take some time, get some space, clear our minds, and seek inspiration. Once we find our inner peace, we will know what to do and understand that things will work out.

• Virginia’s holiday picture from her family is an invaluable contribution because, not only is it the only picture in the book with more than just one person, but it also shows how important it is to have a support system behind every one of us, let it be your family, friends, colleagues, or a professional team.

Collaborating with others and not fighting alone are very moving pieces of advice, and can really help one to progress. The flipbook is testimony to that. After all, so many passionate professionals in the industry came out in full force to support, not only this project, but the future of our industry as well.

• Pictures of Ruth, Layla, Jose, and Mei-Ling show that doing extra-curricular activities actually sharpen your mind and thoughts and make us a stronger and better interpreters!
• The pictures from Rania, Elizabeth (Love What You Do), Lisa, Paulo, and Maria show core elements, skills, and practical tactics required of interpreters.

Last, but not least, we also would like to give thanks to Rania’s contribution. Thanks to her summary of all the major advice, everything fell right into place, which we couldn’t appreciate more. We are proud to echo what Bing says–  “the flipbook is well designed and exceptionally inspiring,” what Elizabeth says – “I am sure it will be a blessing to newcomers and seasoned professionals alike.”

Conclusion: AI vs. Humans

Finally, the conclusion of the flipbook is on pages 14, 15, and 16.

• On page 14, Helena and Sasha identify the elephant in the room –
• Then on page 15, Vanessa challenges AI saying – “if you interpret/translate like a machine, a machine could take your job, but if you bring your humanity into the work, you can really stand out.”
• On page 16, Jose further concludes that –
  “In our fast-paced digital world, the intrinsic human qualities of empathy and warmth remain indispensable in interpretation.”
• “So, continue honing your skills and nurturing those invaluable soft skills – they are your most powerful tools in this profession!”

We were amazed to see that the interpreters provided different perspectives on AI and Humans, and echoed each other so well! The participating interpreters’ conclusion coincides with what Monterey Language Services is convinced of after making 12 videos to compare the performances of professional interpreters to AI.

Wonderful insight and advice

The messages from all these accomplished interpreters with their fingers on the pulse of the industry, with their heartfelt words and their pictures – it’s all really come together to make something special that we’re excited to share with whomever needs to hear it, especially during this time of uncertainty.

We love the awesome quote from Bing “the wealth of information disguised as language”. There’s so much information coded in language, and it’s up to us as interpreters to decode it for others to understand, which is something that machines still fail to master.

We clearly see a bright future for those interested in becoming translators or interpreters! So keep calm and keep going!

“Keep calm and keep going” is a powerful reminder for everyone. Don’t get too much into your head or scramble for a fix, or rush to make progress. Just stay calm, do what you have to do, and carry on. With time, everything will turn out well, naturally. Thanks to Lenne for providing the perfect ending for such a complex undertaking that, as Martha put it, will benefit everyone in the world of languages.

How does AI apply to the language industry? AI has always been a constant question mark in the back of our minds especially regarding automatic translations. Now that AI can do so much, is it time for translators to become worried?

Today, translators use machine translation programs such as Trados or MemoQ to give them a baseline to work from, so called post-editing machine translation (PEMT). PEMT can greatly improve translation times especially for longer translations. For translators, it has been recognized as a valid strategy and working method. However as we all know, the translations that machine translation programs produce aren’t perfect. They are often more than not flawed. But what happens if you begin using AI such as Chat GPT which is designed to produce fluent and natural sounding language? Would a translator have a more powerful tool? Or would you have a competitor?

Translators will find that the answer is the same as it always has, ever since machine translation was introduced into the world. A machine will most certainly not remove the need for a translator. Language is always so fluid, full of nuance and possibilities that it’s almost impossible for a machine to pick up on every last detail. On the flip side though, translators may find a new ally with AI as it can cut their work time, allowing them to work on more projects. For example, translators can enter questions into Chat GPT, maybe have it check for fluency or suggest different ways of phrasing things, or even come up with new ideas.

If you’re an interpreter, you probably have even less to worry about. Though AIs such as Google Assistant are popular for quick and easy phrases, it still runs into the same problems as it is pulling from Google Translate. Interpretation especially is a field where accuracy and nuance is important and a lot of that is easily lost with AI translations.

Overall, in the language field, whether the advancement of AI would replace the role of human translators and interpreters is nothing to be concerned about, at least not in our life time. If anything, we should be excited about it. As the technology advances, translators and interpreters may find a powerful ally that will help them advance their work efficiently.

The Printing Press

It is a little-known fact among the Western world that Johannes Gutenberg was not in fact the first to create a printing press. Borrowing from wood-block printing in many Asian cultures, Korean Choe Yun-ui created the first printing press with moveable block characters in the 1200s. However, due to many factors, such as invasion into Korea and the fact that organizing the Chinese characters to print took quite a while, this printing press did not become widespread.

Gutenberg’s printing press, on the other hand, often printed works written in Latin, which is written with far, far fewer letters than there are characters in Chinese. Arranging the type pieces and going through the printing process was markedly easier than in Korea two hundred years earlier, and Gutenberg’s printing press was essential for the increase in literacy in the following century. In our last blog, we mentioned that Martin Luther’s German translation of the Bible was a major turning point in the history of translation; without the printing press, his translation would not have reached even half the people that it did.

The Rosetta Stone

The Rosetta Stone, first discovered in 1799, held a passage that was written three times—twice in two versions of ancient Egyptian, and once in ancient Greek. The passage, written in 196 BC, was key to deciphering Egyptian hieroglyphics, despite so much of the Rosetta Stone being broken and incomplete.

The Nuremberg Trials

The infamous Nuremberg Trials were held to take Nazis to court and to try them for war crimes that took place during World War II. Remarkably, the trials only took ten months to complete, despite the need to translate and interpret the proceedings into numerous languages. This was accomplished by implementing the world’s first simultaneous interpretation program, which likely saved years off of the Trials’ time. Simultaneous interpretation is difficult to learn the skills for, but is commonly used for conferences, such as for the United Nations.

The Internet

With the advent of the internet, the world became even more global than ever. While learning languages and speaking or writing to a language partner regardless of distance was possible with phone calls and letters, the internet sped up those processes to be nearly immediate.

With this, however, came increasing demands for translation and interpretation for global businesses. Translators and interpreters now had to learn how to not only navigate linguistic landscapes, but also digital ones.

Machine Translation

Very recently in the history of translation and interpretation has been the rise in machine translation. Essentially, putting one string from language A into a machine, which would produce that string in language B. This method vastly improves the speed at which translators can do their jobs, but as machines can’t understand language in the way that humans do, translators and proofreaders are necessary to ensure that the final product doesn’t sound unnatural.

Now

While looking back at history, we also look towards the future. In the past, human history has had lots of events that have influenced today’s translators and interpreters. Many events even had an impact on the world as a whole, such as the printing press and the internet. In the future, there will only be even more AI inventions and events that will shape the translation and interpretation sphere. However, one thing we have seen clearly is that language has been highly varied and shaped by human thought and action; in that vein, we in the translation and interpretation industry are still far, far away from being replaced by machines or robots.

1. Aren’t translators and interpreters the same?

This is a very, very common misconception. Outside of the language service provider sphere, “translator” and “interpreter” can be used interchangeably in most discussions. Such as: “We’ll need a translator at the board meeting” versus “We’ll need an interpreter at the board meeting.”

But just what is the difference between those terms? Simply enough, both “translator” and “interpreter” refer to someone who conveys information from one language to another; more specifically, a “translator” works with written words, while an “interpreter” works with spoken words. Some people are only translators, some are only interpreters, and others are both.

2. Can’t any bilingual person be a translator/interpreter?

A very common misconception (in the workplace especially) is “Billy is bilingual, so he can handle this project and translate/interpret for us.” Just because a person is bilingual (or trilingual or more, even), does not mean that they have the training required to be a proper translator or interpreter.

Imagine that “Billy” speaks Spanish at home, but grew up going to school where the primary language of instruction was English. While there’s a chance he can talk about any subject at home with his family members, a likely scenario is that he will know more about biology in English terms rather than Spanish terms. Unless the conversation were very simple, such as general conversation for travel or something similar, it would be very difficult for Billy to translate or interpret something.

Translators and interpreters go through rigorous training for their respective crafts, and have expanded their vocabularies enough to compensate. Proper translators and interpreters have high-level certifications as well.

3. I know a translator/interpreter who did Assignment X, why can’t they do Assignment Y?

In the language services industry, some translators and interpreters can fall under the category of “subject matter experts.” These people have trained to not just be general translators or interpreters, but have polished their skills to cater to certain types of work.

Take “Billy” from above, for example. Imagine he’s become passionate for being an interpreter, and his other interest in biology spurs him to an interest in medical interpretation. After enough study, focus, and—of course—certification, he becomes a proper medical interpreter and specializes in speaking between doctors and patients about surgeries. He might be able to do general interpretation as well, but because of his deep specialty, he might have trouble if he suddenly needed to interpret for, say, a lawyer discussing a lawsuit.

Just like how doctors and lawyers require separate studies, medical interpreters and legal interpreters also require focused study in their area of expertise. They may have skills that overlap, but generally, it’s best to rely on separate translators/interpreters who are subject matter experts rather than the same one for every single job.

4. Wouldn’t machine translation work well enough?

Short answer: No.

Long answer: Machine translation can certainly help a translator do their work. Computer-assisted translation tools (called CAT tools in the industry) can keep a handy glossary of terms for the translator, and have the memory to provide reference for older, similar translations.

But if we rely only on machine translation, any number of problems can happen. Machines think very differently than humans and might misinterpret context, homonyms, word register, and so on. Computers may be able to perform complex mathematical calculations, but the human brain is hardwired for language. Put simply, a translation from a human is going to sound a lot more natural—and have fewer mistakes—than a simple machine translation.

5. Why does a translation need proofreading? Shouldn’t the translator be enough for that?

Speaking of “mistakes,” mistakes happen. To err is human, after all. Translators need proofreaders for the same reason that a journalist, book writer, or a lawyer needs one. Mistakes concerning facts, grammar, spelling, etc. can easily be made by any sort of writer, and the same goes for a translator.

Having a second pair of eyes does wonders for any written work. A proofreader for a translation can catch errors in spelling, word register, a forgotten period or comma—anything that might have slipped through the cracks. If you want a translation to be as polished as possible, having a proofreader is essential.

One of the most popular tools is those that allow you to do PEMT (post-edited machine translation). If you receive a long document and are on a short deadline, then one of the best things to do is to run it through machine translation first and then work on it from there. The most recognized and possibly used machine translation program is SDL Trados. One reason is that SDL Trados has a vast amount of features and functions.

With all the features and functions that SDL Trados comes with, naturally it is much more complex and difficult to learn to use than other, simpler machine translation programs such as Memsource, Wordfast, or Google Translator’s Toolkit. There are also programs such as MemoQ who have been gaining their own following of people who would prefer them to SDL Trados due to certain features or ease of use. However, if you have the time to learn SDL Trados and become able to use it effectively, then it can open a lot of doors for you to do many things.

Aside from machine translation, translators of websites can also rest assured that there are easy ways for them to translate webpages for clients. For instance, if a website is WordPress based, you can ask the client to install a plugin such as WPML. With WPML, all they will have to do is export the target page or post that they want to have translated as an xliff and send it to you, the translator. Once you receive it, you can open it in one of the machine translation programs that were discussed above and insert your translations as if it was a bi-column word file. Then after you are done, you can just send the client back the xliff file and they can import it back into their websites and the translations will be there as if by magic. The great thing about most of these kinds of plugins is that they are simple to learn and once you do learn them, they will save you a lot of time. If the website is not WordPress, there are other programs that you can explore and some webhosts even come with their own built-in language support.

There are many different types of specialized tools that will best fit the kind of translation job that you are working. Therefore, it is important for us as translators to stay updated and in the loop of technology that is being updated or developed regarding what we can take advantage of as translators. This way we can rest assured to do better work and help more people in need of translation.

One way is automating it. Some of the simplest mistakes that translators make involve mixing up numbers, conversions, or names. The easiest way to make sure that you have correctly reflected every instance mentioned in the source in the translation is to use a text compare. Of course, your translation will be flagged as being vastly different from the source, but it will let you know if the numbers, company names, and other words or numbers that have to be the same in the target as they are in the source are the same or not. It also takes virtually no time too. All you have to do is copy and paste then press a button. It shouldn’t take you more than five minutes to go through everything depending on the length of your project.

Another way is to make it hard to make any mistakes from the very start. If you are translating into a new, blank document, instead try translating into the target document itself. You could even enter the strings into a machine translation so that you can see the translation and the source side by side. Doing this makes it much harder for you to make any typing errors when copying whatever needs to be the same in the target as in the source. If the document you have is not easily copied such as a pdf, you can use OCR to help make the text selectable and then copy it into a word document.

The next tip is the simplest and possibly the most obvious solution. Whenever you see something that has to stay the same between the source and target, just copy it from the source to the target. So for example, if you have a number like 1,000,231, then just copy it into the target. If you want to take this a step further, then you should highlight every instance of numbers or text that need to be the same between the two files and then you will be able to quickly identify the places that need to be checked before delivery.

Quality Assurance is a necessary part of the translation process but often not something that is effectively done due to time constraints or other factors. Hopefully with this post, you have learned a few tips about how you can make the process shorter, but without sacrificing any quality. If you are able to submit a translation that avoids minor mistakes can really help your reputation and make you stand out as a translator who can be relied on.

The first one is how to search for an exact phrase. While a dictionary can provide the exact word you want, there are often times where the word might not be used the way you think it should be, or there might be specific contexts in which it can be used or it might just be an outdated term altogether. To find out if a word or phrase you want to use can be used the way you want it to be, you can perform a Google search and put the term or phrase in quotation marks. So, for example, if you wanted to search for only the phrase raining cats and dogs, you could put it in quotation marks, “raining cats and dogs,” and then every single result will be websites that have the words in that exact order. You can also use the “verbatim” search function to search for only the word that you enter.

Next, if you want to find alternatives to words in phrases, you can use Google to search for alternatives. For example, if you wanted to search for different types of machine translation in one search, you could search like this: neural OR statistical OR rule-based machine translation. When you do that, Google will generate search results for machine translation that includes the words neural, statistical, and rule-based. This is handy if what you are searching for has numerous variations to it, but you only need a few alternatives as opposed to all of them.

On the flip side, there is a way to exclude search results from appearing. So in the case that you want all the different variations of a phrase but not something else, then you can use the minus sign to exclude the results that you don’t want. So if you want all the different kinds of machine translation, but don’t want statistical machine translation, then you can search –statistical machine translation and it will exclude all mentions of statistical machine translation. This is great if you know that you don’t want a search result to appear and are looking for other things instead.

One of the simpler tricks that does not require any special input is just comparing the amount of results that one version of a phrase generates versus another. So if you were wondering which spelling of versus is more commonly used, you could search for “vs” first and see how many hits are generated and then search “versus” and then see how many hits are generated. After comparing which one generates more, you can more confidently say that the one with more hits is the more commonly used word and therefore, safer to use in your translation.

The last trick is searching within a specific website for a specific phrase. If you wanted to look for the phrase “machine translation” on SDL’s website for example, you could search it as follows, site:sdl.com “machine translation” and then Google will generate all the instances of machine translation being mentioned on SDL’s website.

How the neural network works and defines the inputted numbers to produce an output is perfected by training the network with millions of sentence pairs. So for example, if you are trying to train a Neural Machine Translation engine for English to Spanish, you would need to feed the engine a great deal of data to help tweak and refine its framework and make it more accurate. Each sentence pair that is given to the engine slightly modifies the neural network while it uses an algorithm called back-propagation. Back-propagation consists of fine-tuning the error rate that comes from the previous iteration. By properly tuning, the error rates can be reduced and the accuracy can be improved.

So what is the advantage of using Neural Machine Translation? Some of the biggest limitations of other machine translation is that they have difficulty when it comes to more complex or nuanced phrases. However, with Neural Machine Translation, it becomes much more possible to translate these kinds of phrases since the number of parameters and rules that can be given provided are much greater and therefore it is more possible to generate translations that are much more natural sounding and closer in meaning.

Neural Machine Translation is without doubt the future of Machine Translation, but there are still reasons as to why it is not widely being adopted. The biggest reason is the sheer cost and time sink that the engines require to actually become useful. As mentioned earlier, millions of sentences need to be entered into the engine for it to start to really output translations that can be considered good quality, and that means using more manpower and time. Not every company is able or willing to invest that many resources to develop a Neural Machine Translation engine, and that is perfectly understandable when weighing the cost versus the reward.

Overall, Neural Machine Translation is a complicated system, but has the most potential out of all of the Machine Translation methods. It is very possible that Neural Machine Translation will be developed to the point where it can accurately be used in a variety of situations for which it is specifically trained, but it is unknown when exactly that might happen. There have been many advancements in its development, but due to its cost and time consumption it will be quite some time before it will be able to be commonly used.

First, there is Statistical Machine Translation, or SMT. The best example of statistical translation is Google Translate. SMTs such as Google Translate use statistical models that draw on a large amount of bilingual text that is provided to them. Through this, they try to find statistical matches for how many times something has been translated as something. For example, if the word “apple” has been translated as “manzana” in Spanish enough times, then that becomes the SMT’s pick for the word apple. It does this for every word in the source and target language before it finally outputs a translation. SMTs can be useful for translating basic words and phrases. However, for more complex sentences, SMTs are not a good pick because they do not factor in context. This means that you can end up with some very strange sentences that do not properly reflect what is being said in the source sentence.

Next, there is the Rule-Based Machine Translation, or RBMT. As the name implies, with RBMT, the machine is translating based on the rules of grammar that it is given. It goes over the source language to analyze its grammar and then looks through the target language to see what kind of grammar rules need to be followed when translating the sentence. After it is done, it translates the sentence according to the rules that it looked up. While this might sound as if there might be fewer problems than SMTs, RBMT translations still need a great deal of proofreading to ensure that there are no problems with the text.

Third, there is the Hybrid Machine Translation, or HMT. The HMT takes elements of RBMTs and SMTs and then uses a translation memory. The addition of a translation memory makes the overall quality of the translation higher than that of SMTs and RBMTs, but there are still problems with using a HMT. For one, it still needs extensive editing, meaning that human translators will be needed to review all the translations.

The fourth, and final type of translation is Neural Machine Translation, or NMT. This type of machine translation uses neural network models that are based on the human brain to make statistical models for translation. When they work, NMTs can provide some of the most accurate translations that would need little to no editing potentially. One of NMT examples is DeepL.

Overall machine translation can be used as a tool to expedite translation, but whether it can produce clear and accurate translation for high level discussions, complex concepts, nuances and context that is still in question and requires time to advance it. This once again proves that the value of professional human translators is not replaceable just yet!

This opinion has only been further enforced in the light of the current pandemic. With social distancing being encouraged, many businesses and individuals are moving away from face-to-face business and moving to the safety of digital solutions. With many people preferring in-person interpretation, and less interpreters willing to ignore safety conventions to fulfill these requests, there are some who would prefer to try machine translation.

In this day and age, there are sophisticated machine translation engines that can even almost do simultaneous interpretation. If the subject is within a specific, technical subject, the accuracy of the outputted translation goes up as well. Many would point to this as being the time for machine translation to rise in popularity and use.

Even so, businesses still tend to prefer using interpreters when they can. There is, and will most likely never be a true replacement to a human interpreter. In fact, interpreters were already still able to work remotely even before the pandemic. With Zoom and over-the-phone interpretation, interpreters are still able to work without too much of a change to the experience.

Of course, there are still some difficulties and annoyances with remote interpretation, but it is still the most reliable and preferred method for interpretation. The same applies for translation. Most translation has been done remotely, and is still preferred over machine translation for the same reason businesses prefer human interpreters. Though machine translation is a powerful tool, it is still not reliable or trusted enough to fully replace the human touch. During this pandemic, the work of translators and interpreters may be affected, but it is not because of a rise in machine translation.