This is an unsolicited guest post that provides a view of translation technology that is typical of what is believed by many in the translation industry.
These initial preamble comments in italics are mine.
It provides an interesting contrast to the previous post (Ending the Globalization Smoke Screen) on the need for LSPs to ask more fundamental questions and climb up higher in the value chain and contribute higher value advice on globalization initiatives. This is a view that sees the primary business of LSPs, and thus the role of technology, as being the management and performance of human translation work as efficiently as possible.
These initial preamble comments in italics are mine.
It provides an interesting contrast to the previous post (Ending the Globalization Smoke Screen) on the need for LSPs to ask more fundamental questions and climb up higher in the value chain and contribute higher value advice on globalization initiatives. This is a view that sees the primary business of LSPs, and thus the role of technology, as being the management and performance of human translation work as efficiently as possible.
I think we have already begun to see that the most sophisticated LSPs now solve more complex and comprehensive translation problems for their largest customers, which often extends much beyond human translation work. In December 2016, the new SDL management reported that they translate 100 million words a month using traditional TEP human translation strategies, but they also translate 20 billion words a month with MT. The VW use case also shows that for large enterprises, MT will be the primary means to translate the bulk of the customer-facing content, in addition to being the dominant way to handle internal communications related translations. Clearly, much of the translation budget is still spent on human translation but it is also much clearer that MT needs to part of the overall solution. MT competence is valuable and considered strategic when choosing an agency, and by this, I don't mean running sub-standard Moses engines. Rather, it is about working with agencies who understand multiple MT options, understand corpus data preparation and analysis and can steer multiple types of MT systems competently.
Aaron raised what I think are many very interesting questions for the "localization" industry. How do we as an industry add more value in the process of globalization, and he suggests quite effectively I think, that it has more do with things other than using basic automation tools to do low-value things more efficiently. The globalization budget is likely to be much higher than the translation budget and involve answering many questions before you get to translation.
It is also my sense that there is a bright future for translation companies that solve comprehensive translation problems (i.e. MT, HT, and combinations), help address globalization strategies, or perform very specialized, high-value, finesse-driven human translation work (sometimes called transcreation, an unfortunate word that nobody in the real-world understands). The future for those that do not do any of these things I think will be less bright, as the freely available and pervasive automation technology that is available for business translation tasks will get easier to use and more efficient. The days when building a TMS to get competitive advantage made sense are long gone. Many excellent tools are already available for a minimal cost and it is foolish to think that your processes and procedures are so unique as to warrant your own custom tools. The value is not in the tools you use but how, when, and how skillfully you use them. Commoditization happens when the industry players are unable to clearly demonstrate their value add to a customer. This is when price becomes the prime determinant of who gets the business, as you are easily replaceable. This also means that you are likely to find that the wind is no longer in your sails and it is much harder to keep forward momentum. In the post below, the emphasis is not mine.
=======================================
↓↓↓↓↓
What’s out there, and what’s to come?
Technology is improving all the time. Technological advances like Artificial Intelligence (AI), Virtual Reality (VR) and the advance of smartphones are rousing the public’s interest.
It’s the same for translation technology. The way we translate and interpret content is changing all the time. Reliable translation technology is making it easier, faster and more productive to do our jobs.
Take for instance machine translation (MT). We see this type of technology as more of an additional language service to enable more content to be translated – rather than as a substitute language service to replace human translation.
MT is often considered in circumstances where the volume of content requiring translation cannot realistically be approached as a human translation task, for reasons of cost or speed. In this setting automatic translation can be deployed as part of a wider workflow.
Technology like this, for example, may enable a company to translate millions of words of user-generated content which would otherwise be completely out of reach. MT would not, however, be advisable for public-facing content, such as press releases.
Machines that translate
The benefits of machine translation largely come down to two factors: it’s quicker and less expensive. The downside to this is the standard of translation can be anywhere from inaccurate, to perplexing – machines can’t translate context you see.
The disadvantages as noted above can be avoided if the machine translation is checked by a professional. The last thing you want is a call from a lawyer telling you you’ve mistranslated one of their clients’ quotes.
Machine translation consists of rules-based systems that generate a translation by combining a vocabulary of words with syntactical rules. Whereas with statistical MT, the engine is fed with large volumes of translations that are analyzed using pattern-matching and word-substitution to predict the translation which is statistically the most likely to be correct.
It can be argued that machine translations are more suited to internal use, if your documents are only being used within your company, complete accuracy may not be vital. Another example would be for very basic documents – the more simplistic your original documents are, the easier they will be for a machine to interpret.
You need to be certain there is ample precision in your machine translations to hurry up the process. Otherwise, it will only slow the progression down and you’ll attain very little by using it. Machine translation is a time-saving tool – if it doesn’t do that, then it’s not worth using, or at least no solely relying on. That’s not to say that machine translation isn’t vital in some cases. It certainly is, more on that later.
Human translation basically shifts the table in terms of pros and cons. A higher standard of accuracy comes at the price of longer turnaround times and higher costs. What you have to decide is whether that initial investment outweighs the potential cost of errors.
More creative or intricate content such as poems, slogans or taglines ask far too much of machine translation tools so it’ll always make sense to opt for a human translator. When accuracy is paramount, take, for example, legal translation, safety instructions, and healthcare, machines leave far too much room for error.
Another point to make when deciding if it’s appropriate to use human over machine translation is when there’s not sufficient accuracy for machines to work with. If the content is too chaotic then it may be easier for a human translator to work and edit the original text – machine-free.
The translation of content is attainable using machine translation don’t get me wrong, for example, when translating high-volume content that changes every hour of every day – humans just can’t keep us and it would cost far too much. But if you require full control of your communication then a human translator is the better option – granted that the task isn’t too large or would not be obtainable without using MT.
In the machine versus human translation debate, the latter has the edge – for now anyway – because the translator can provide a more accurate translation of your message.
This aside, companies like TripAdvisor and Amazon rely on machine translation because their online content and the daily visitors to their websites are so vast. Machine translation gives them the chance to stay up-to-date and offers users multilingual content rapidly. Companies like these would find that solely relying on humans to translate their message a demanding if not impossible task.
Machine translations have their place in the world – it’s an important place for sure – and can deliver the basic meaning of a text when your company is in a bind. However, cannot live up to the quality of a human-powered translation, which is the service you should choose when you want an official communication of your company to be fully understood by its readers.
I want translation now
Moving swiftly on, advanced translation software which allows its users to centralize all their translation requirements, making it simple to tailor translation workflows is translation management systems (TMS). Though nothing new anymore, software like this is not only saving people time but the automated processes mean it saves money too.
Larger companies are opting for one easy-to-use TMS platform in order to have complete control over their translation workflows. The software gives users a 360-degree overview of every current and completed translation job submitted. A TMS platform also gives users real-time project status information.
Moreover, creative translation tools allow teams of graphic designers and creative agencies to use web browsers rather than costly Adobe packages to review INDD or IDML content. Translation technology like this means no extra license fees to pay when localising and reviewing content.
Reviewers who do not have InDesign installed on their systems can see a live preview, edit text so it is exactly how they want it, and save their changes so that the InDesign file is updated. Tools like this give users peace of mind in the knowledge that the InDesign document cannot be “broken”, and that no time is spent copying and pasting text, or trying to decipher reviewers’ comments, or having to repeatedly transfer files backward and forwards.
As technology improves so does the expectations of its consumers. People want their information fast. When it comes to translation, in an online sense specifically the content needs to remain up-to-date and be easy to find. TMS platforms can be integrated with websites, CMS, DMS and database applications – this makes them an essential part of translation services.
Big technology brands like Apple and Google offer translation services of their own. iTunes and Google Play allow you to download transcription apps, giving you your own personal translator in the palm of your hand.
They’re handy devices but useless if you need accurate voice recognition and more than a few sentences transcribed. Your main concern with any transcription app will always be accuracy. You want the device to understand every word you say and accurately type it out in text form. Well, unfortunately, this is where the technology continues to fall way short of the demand.
Technology has evolved. But we’ve been evolving too and we still have a few tricks up our sleeves. A mother-tongue translator is still the only sure-fire way to ensure the most natural reading target text. It’s arguably the best way to get the most relevant translation possible. Language services companies still receive far more human translation inquiries. More than 90% of job requests are for human translation.
What’s next?
In the realm of AI for instance, a lot. Take for instance AI web-design software and an increasing list of automated marketing tools hitting the scene. All hoping to make translation services a more streamlined process – one that’s faster, cheaper and demands less manpower to make things happen.
Personal assistant apps such as Apple’s Siri and Amazon’s Alexa are driving online business in a way never seen before. These AI-powered apps are also changing web localisation in a huge way. More than ever businesses need to be aware of third party sites like Google Maps, Wikipedia, and Yelp because apps such as Microsoft’s Cortana are pulling snippets of content from all around the web.
According to Google Translate’s FAQ section, “Even today’s most efficient software cannot master a language as well as a native speaker and have by no means the skill of a professional translator.”
If the technology available helps. If it saves us time, money and precious resources then surely it’s vital and something we should be taking advantage of. But at the same time, most of the translation technology available to us should be used wisely. Often than not it should be used as a tool to aid us, not necessarily something to be relied upon.
Don’t get me wrong, I’m not for a second lessening the importance of machines when it comes to translation services. All I will say is that human translators are more familiar with expressions, slang, and grammar of a modern language. Often human translators are native speakers of the target language which gives greater depth and more of an understanding of the tone of the required translation.
Human translators also boast translation degrees, some specialise in a specific area of expertise and their understanding in the field of the project expedites the translation. Although it’s safe to say, one type of language translation that still baffles the most educated of linguists is emojis.
The multifaceted landscape of interpreting symbols makes translating these icons tough for both machines and humans – fact.
These ideograms are actually making it to court cases where text messages are regularly being surrendered as evidence. So it’s paramount that context and the interpretation of each emoji is understood.
The meanings of each smartphone smiley are often unclear and sometimes puzzling. This leaves far too much for misunderstanding, in fact in 2016 professional translators from around the world attempting to decipher emojis and the results were miserable.
Technological advances in the translation industry are going to change the way businesses operate for the better. Even though some of it threatens to compete against us, we fully expect this to continue and start happening in a much wider range of industries.
Machine translation services will play a vital part in producing multilingual content on a large scale. Big brands that need content fast, in large quantities will opt for MT. In fact, more and more professional translators will need to adapt to working more closely with this technology as it advances over time.
For things like AI, VR and apps the future is prosperous. We’re entering a world in which we take technology for granted. What’s capable nowadays and what will be in the future will aid us, maybe even guide us one day. But for the time being – though essential – the translation technology at our disposal still fails to deliver what humans are fully capable of.
= = = = = = = =
Tom Robinson, Digital Marketing and Communications Executive at translate plus, a Global Top 50 language services provider by revenue, offering a full range of services, including translation, website localisation, multilingual SEO, interpreting, desktop publishing, transcription and voiceover, in over 200 languages. All this is complemented by our cutting-edge language technology, such as i plus®, our secure cloud-based TMS (translation management system).
