Tag: Translators

A Beginner’s Guide to Machine Translation

A Beginner’s Guide to Machine Translation

What is Machine Translation?

Machine translation (MT) is automated translation by computer software. MT can be used to translate entire texts without any human input, or can be used alongside human translators. The concept of MT started gaining traction in the early 50s, and has come a long way since. Many used to consider MT an inadequate alternative to human translators, but as the technology has advanced, more and more companies are turning to MT to aid human translators and optimize the localization process.

How Does Machine Translation Work?

Well, that depends on the type of machine translation engine. There are several different kinds of MT software which work in different ways. We will introduce Rule-based, Statistical, and Neural.

Rule-based machine translation (RBMT) is the forefather of MT software. It is based on sets of grammatical and syntactical rules and phraseology of a language. RBMT links the structure of the source segment to the target segment, producing a result based on analysis of the rules of the source and target languages. The rules are developed by linguists and users can add terminology to override the MT and improve the translation quality.

Statistical MT (SMT) started in the age of big data and uses large amounts of existing translated texts and statistical models and algorithms to generate translations. This system relies heavily on available multilingual corpora and an average of two millions words are needed to train the engine for a specific domain – which can be time and resource intensive. When a using domain specific data, SMT can produce good quality translations, especially in the technical, medical, and financial field.

Neural MT (NMT) is a new approach which is built on deep neural networks. There are a variety of network architectures used in NMT but typically, the network can be divided into two components: an encoder which reads the input sentence and generates a representation suitable for translation, and a decoder which generates the actual translation. Words and even whole sentences are represented as vectors of real numbers in NMT. Compared to the previous generation of MT, NMT generates outputs which tend to be more fluent and grammatically accurate. Overall, NMT is a major step in MT quality. However, NMT may slightly lack behind previous approaches when it comes to translating rare words and terminology. Long and/or complex sentences are still an issue even for state-of-the-art NMT systems.

The Pros and Cons of Machine Translation

So now you have a brief understanding of MT – but what does it mean for your translation workflow? How does it benefit you?

  • MT is incredibly fast and can translate thousands of words per minute.
  • It can translate into multiple languages at once which drastically reduces the amount of manpower needed.
  • Implementing MT into your localization process can do the heavy lifting for translators and free up their valuable time, allowing them to focus on the more intricate aspects of translation.
  • MT technology is developing rapidly, and is constantly advancing towards producing higher quality translations and reducing the need for post-editing.

There are many advantages of using MT but we can’t ignore the disadvantages. MT does not always produce perfect translations. Unlike human translators, computers can’t understand context and culture, therefore MT can’t be used to translate anything and everything. Sometimes MT alone is suitable, while others a combination of MT and human translation is best. Sometimes it is not suitable at all. MT is not a one-size-fits-all translation solution.

When Should You Use Machine Translation?

When translating creative or literary content, MT is not a suitable choice. This can also be the case when translating culturally specific-texts. A good rule of thumb is the more complex your content is, the less suitable it is for MT.

For large volumes of content, especially if it has a short turnaround time, MT is very effective. If accuracy is not vital, MT can produce suitable translations at a fraction of the cost. Customer reviews, news monitoring, internal documents, and product descriptions are all good candidates.

Using a combination of MT along with a human translator post-editor opens the doors to a wider variety of suitable content.

Which MT Engine Should You Use?

Not all MT engines are created equal, but there is no specific MT engine for a specific kind of content. Publicly available MT engines are designed to be able to translate most types of content, however, with custom MT engines the training data can be tailored to a specific domain or content types.

Ultimately, choosing an MT engine is a process. You need to choose the kind of content you wish to translate, review security and privacy policies, run tests on text samples, choose post-editors, and several other considerations. The key is to do your research before making a decision. And, if you are using a translation management system (TMS) be sure it is able to support your chosen MT engine.

Using Machine Translation and a Translation Management System

You can use MT on its own, but to get the maximum benefits we suggest integrating it with a TMS. With these technologies integrated, you will be able to leverage additional tools such as translation memories, term bases, and project management features to help streamline and optimize your localization strategy. You will have greater control over your translations, and be able to analyze the effectiveness of your MT engine.

Reference: http://bit.ly/2P85d7P

TRANSLATION TECH GOES MEDIA

TRANSLATION TECH GOES MEDIA

Four out of the five fastest-growing language services companies in 2018 are media localization specialists. The media business has seen a boom over the last two years, and traditional translation companies are taking notice. Media localization won’t stay an uncontested insular niche for long. In fact, conventional LSPs and technology providers are moving into this sector and expanding their technical capabilities this year.

HERE ARE A FEW EXAMPLES, WITH MORE TO FOLLOW…

Omniscien launched an automated subtitling tool

Omniscien, previously Asia Online, is best known for its trainable machine translation software, but now they are going into a new area – video subtitling. Omniscien has just started selling Media Studio, which was built based on product requirements from iflix, a Malaysian competitor to Netflix.

Under the hood Media Studio has machine learning components: audio transcription, dialog extraction, and neural MT engines pre-trained for subtitles in more than 40 language combinations. The technology is able to create a subtitle draft out of a raw video already in the target language. It can even adjust timings and split long sentences into multiple subtitles where necessary. And it’s learning all the time.

For the human part of the work, Media Studio includes a web-based subtitle editor and a management system, both including a significant range of features right from the start. Translators can edit time codes in a drag-and-drop fashion, skip parts of the video without speech, customize keyboard shortcuts, and more. Project managers can assign jobs and automatically send job notifications, track productivity, and MT leverage.

The video is hosted remotely and is streamed to linguists instead of sending complete films and episodes. This adds a security layer for the intellectual property. No one in the biz wants the next episode of the Game of Thrones to end up on thepiratebay.org faster than it would on a streaming service. Linguists in low-bandwidth countries can download videos in low quality and with a watermark.

On the downside, this new tool does not integrate with existing CAT and business management systems for LSPs out of the box, doesn’t have translation memory support or anything else that would make it fit as one of the blades in the Swiss army knife of LSP technology.

According to Omniscien’s CEO Dion Wiggins, iflix has processed hundreds of thousands of video hours through the system since its inception in late 2016. By now, three more large OTT providers have started with Media Studio. Content distribution companies are the main target for the tool, but it will be available for LSPs as well once the pricing is finalized.

GlobalLink deployed subtitle and home dubbing software

At a user conference in Amsterdam this June, TransPerfect unveiled a new media localization platform called Media.Next. The platform has three components:

The subtitle editor is a CAT-tool with an embedded video player. Translators using this platform can watch videos and transcribe them with timings, possibly with integrated speech recognition to automatically create the first pass. As they translate using translation memory and termbase, they are able to see the subtitles appear on the screen.

The home dubbing is all about the setup on the voice-actor side. TransPerfect sends them mics and soundproofing so that recording can happen at home rather than at a local audio studio.

A media asset management platform stores videos at a single location and proxies them to the translator applications instead of sending complete files over the Internet, similar to Omniscien’s approach.

The official launch of TransPerfect’s Media.NEXT is scheduled for mid-August.

Proprietary tech launched earlier this year

TransPerfect’s tech is proprietary, meant to create a competitive advantage. Media localization companies such as Zoo Digital and Lylo took a similar approach. They have launched cloud subtitling and dubbing platforms, but continue to keep technology under the radar of other LSPs.

The idea of “dubbing in the cloud” is that it gives the client visibility into the actual stage of the process, and flexibility with early-stage review and collaboration with the vendor. The same idea permeates Deluxe Media’s platform Deluxe One unveiled in April this year. It’s a customer portal that provides clients with access to multiple services and APIs.

Deluxe One user interface

MemoQ and Wordbee add view video preview for subtitling

At the same time, subtitling capabilities are beginning to make their way into tools that are available to hundreds of LSPs around the world.

Popular translation editor memoQ has added a video player with a preview in their July release. The editor now opens the video file at the point that is being translated and displays the translated text so that translators can check it live. It can also show the number of words per minute, characters per second, or characters per line.

A similar preview appears in Wordbee. The embedded video player can open videos from an URL, or play clips that are uploaded to the editor directly. The initial release includes a character limitation feature to keep subtitles concise, and anchoring: clicking on the segment with the text rewinds the video to that text.

This is a step showing memoQ’s and Wordbee’s move deeper into media, and differentiating them from other TMS.

So far, few TMS had video previews, one of them was Smartcat. Subtitling functionality in Smartcat has been developed in 2013 for a special project, crowdsourced localization of e-learning platform Courserra. Today, users need to enable subtitling functionality on request. The feature set available includes a video player, timecode parsing, and anchoring. Subtitling user numbers in Smartcat are rising, according to product manager Pavel Doronin.

Back to memoQ and Wordbee, their development teams probably will need to expand the list subtitling features over time: first of all, timecode editing. Moreover, memoQ and Wordbee support .SRT extension, whereas Omniscien’s tool supports TTML as well: a more advanced format that allows manipulating subtitle colors, position on screen and formatting. TTML might become more important for video on demand work and streaming platforms, for instance, it is the format that Netflix uses.

Future “luxury” features could include character tracking with descriptions explaining their voice and preferred vocabulary, support for the speech-to-text technology, audio recording, etc.

Subtitling commoditization looms

Subtitling is not new to the translation industry, and almost every mature CAT/TMS supports .srt SubRip text files. However, linguists have to run a third-party video player in a separate window to see their work. They also have to reload and rewind every time to see changes in the subtitles.

That’s why in professional scenarios, subtitlers often use Amara, Subtitle Workshop, Oona captions manager, CaptionHub or similar specialized tools. These tools came from outside the language industry and didn’t support translation memories, term bases, and embedded MT.

Previous attempts to create tools that combine the best of two worlds didn’t quite meet with commercial success. Years following the launch, user numbers for dotsub.com, hakromedia SoundCloud, and videolocalize.com stayed limited. So far, most language industry professionals viewed media localization as a niche service rather than as a growth area. As a result, they didn’t invest in specialized departments and software. But with video content increasing in share, and with media companies demonstrating record revenues, this might eventually change.

However, by the time it does change, translation tools may achieve a “good enough” capability. Fast-forward 1-2 years – most LSPs might be able to subtitle without extra investment or training. It will become even easier to enter into subtitling and compete, leading to price pressure. Subtitling may turn into an even more crowded and low-margin space before you can say “commoditization”.

Dubbing: Home studio vs studio M&A strategy

Dubbing, on the other hand, is a different kind of deal.

So far, the dubbing market has been dominated by larger companies such as Deluxe and SDI Media that provide voice talent in physical sound studios located in multiple countries. Perhaps one of the best examples of this would be Disney’s Let It Go which has been translated into at least 74 languages.

Infrastructure for such projects is costly to build and maintain. Brick-and-mortar studios have high bills and need a constant flow of work to stay profitable. Projects might be hard to find for second-tier language outlets. To have a French studio overloaded and a Croatian studio suffering losses year after year is a realistic scenario for a network company.

The virtual/home studio approach being used by newer players in this field such as TransPerfect, Zoo Digital and Lylo Media, is more scalable and provides acceptable quality for most clients. But will it be enough for high-profile content owners that award the largest contracts?

If the home studio approach produces sustainable growth, commercial software vendors will jump in and replicate the technology, leading to lower entry to dubbing. However, if it fails over 2018-2019, instead M&A will become the go-to-market strategy in the media localization space. Watch out for smaller studio acquisition frenzy!

Reference: http://bit.ly/2LVhf6C

Translating in-house? Here’s what you need to know

Translating in-house? Here’s what you need to know

How does your law firm get translations done? If you do some or all of it in-house, you may run your own translation team; rely on the language skills of lawyers, knowledge managers and other colleagues; or use a combination of the two.

Given the ever-present need to work as efficiently as possible in order to meet delivery deadlines, we’ve seen a number of ways in which law firms try to speed up their in-house translation process. Here are a few of the things they’ve learned along the way:

Be wary of manually reusing content

Translators may look to reuse content from previous translations by copying and pasting chunks of text. It’s an exceedingly common practice — but one that’s fraught with danger. Just as with drafting precedents, starting with existing documents risks missing subtle differences between cases — and horror stories abound of the consequences of these errors (including houses being sold to the wrong person). The end result: most of the time saved reusing content could well be spent fixing errors (either those caught internally or spotted by your client).

Many hands make light work?

Another option is to split a document into sections for several colleagues to work on concurrently. This may be faster and may reduce the chance of errors when compared to reusing old documents, but it raises concerns around consistency between different translators. It also means great care must be taken when the translated document is stitched back together at the end of the process.

Free tools come with a cost

It may be tempting to turn to free online translation tools like Google Translate to make the work go faster, especially for small jobs like birth certificates or even tweets. But law firms are generally against the idea — and understandably so. For starters, free tools aren’t designed to translate complex legal terminology, or to render legal concepts from one jurisdiction to another — so there’s no guarantee of quality or accuracy. Reviewing and amending the translated output could therefore take more time than doing the work from scratch. Besides that, using such tools could put confidential or valuable information at risk.

The right technology is a lifesaver

One reason many law firms struggle to get translations done quickly, accurately and consistently is that they’re doing the work using standard office productivity apps. But as these apps aren’t designed with translators’ needs in mind, they don’t include the features needed to make translation an efficient process.

That’s why you’ll find that firms who are translating in-house successfully are often using computer-assisted translation (CAT) tools.

CAT tools are designed to help translators work faster and smarter. Using technology developed specifically to support translation work, it can:

  • Raise quality and consistency, and accelerate handling of repetitive content, with translation memories and terminology databases that simplify reuse of previously approved content
  • Increase translators’ productivity with features to increase the speed of translation while safeguarding against mistakes
  • Turn lengthy documents round faster by making it easy for several people to collaborate on the same translation

Balance speed, quality and cost

At the end of it all, the translation challenge comes down to three variables: cost, quality, and speed. Just as with the outsourcing model, translating in-house brings unique challenges to maintaining the balance between these three variables.

CAT tools can help law firms tip the scales in their favor, by giving them a way to improve speed without compromising on quality.

Reference: http://bit.ly/2OgpXcg

Why People Leave the Language Industry

Why People Leave the Language Industry

Working in a language service provider (LSP) can be an exciting and challenging place to be: managing complex projects, figuring out best workflows, delivering to demanding deadlines, working with teams of people from diverse cultural and linguistic backgrounds… But what motivates people who have studied languages and translation to leave behind a career in the language industry? And where are they now?

Slator conducted a number of interviews and spoke to individuals who had all worked for 3+ years in a sales or operational capacity within a language service provider in either France or the UK. All had studied languages and / or translation to degree or post-grad level.

Respondents revealed that they were originally attracted to the language industry for a variety of reasons, including the appeal of a “multicultural environment” coupled with a “passion for languages”, “the ability to be able to communicate without borders”, having the opportunity to use languages on a daily basis and “learning more about…the art of translation and culture surrounding the language.”

The aspects of their roles that they enjoyed most ranged from “the camaraderie and internationalism” to “client side, travel and coaching people” and the fact that “it was always busy and fast-paced which kept me on my toes.”

International Environment

Asked what they liked about the companies (LSPs) they worked in, one respondent identified “the feel you were doing something important for large clients” and another said that she had worked in “a small company and became friends with colleagues”. Again, “international environment” and “international focus with different office locations” featured prominently.

On the benefits of the industry as a whole, one respondent said she “learned a lot about finance and legal, practicing at least two languages daily”. Innovation and technology also contributed to the appeal: “it is forever evolving and has an exciting future ahead,” one said, while another thought that “interesting technology advances” were a distinct positive.

So, despite the lure of an international and evolving market, where you can meet people and travel, what factors are leading individuals to leave the industry in favor of alternative careers? And what opportunities are they seeking out?

Why People Leave

We asked respondents to describe their reasons for leaving the language industry in their own words. One person, who worked for six years in project management, said that it was “impossible to progress, [there was] no reward for going the extra mile, [and] no human contact”.

Another, who spent three years in the industry in a project management role echoed this sentiment, saying that “I found I’d reached a plateau, both in terms of pay and also in terms of what my job entailed (it became quite samey)”. She went on to say “I figured my skills could be transferred into another sector which could offer more variety and options for the future”.

60% of respondents cited lack of progression for the primary reason for leaving.

One individual saw few differentiating factors between LSPs saying “I felt that most LSPs were much of the same and there was little difference between being a project manager at any of them. I decided to leave to travel for a few months and didn’t feel like I wanted to return to the same career.” Yet another thought that “the progression was too slow. Individuals were being overloaded and therefore project standards were slipping.” One person identified a culture of blame in the company he left behind to pursue a teaching career.

Only one respondent gave reasons that were uniquely “pull factors” and said that she had left “to pursue other avenues in a different field and focus on the transferable skills gained during my time at the various LSPs, notably, leadership and coaching” after 13 years in the industry.

When pressed, 60% of respondents cited lack of progression for the primary reason for leaving, with comments including “impossible to progress”, no “options for career progression” and “being overlooked for promotion”.

Stepping Stone to Another Career

A few interview questions centered on the respondents’ experience of pursuing a new career – how easy did they find it to secure a new role and how had working the language industry prepared them for a new line of work.

Most (80%) felt that the skills they had acquired were relevant to other industries. And the respondents had moved into a variety of roles and industries, from HR and Recruitment to Wine Buying, Events Coordination for a cloud networking company, Supply / Logistics, Marketing and Teaching.

Most found it “quick”, “easy” or “relatively easy” to find a new role, suggesting that language industry leavers are in high demand across a wide range of industries.

Most (80%) do not regret the decision to leave, while 20% are unsure (perhaps because it is still early days), but none are openly dissatisfied with their choice to pursue a different career. Similarly, none could foresee returning to the industry out of choice, e.g. “I hope it does not happen, but if it does, it will be for a short time as I am not willing to stay in this industry.”

The exception to this seemed to be the possibility of returning in the capacity of a freelance linguist: “The flexibility of being a freelance translator might tempt me at some point in the future. (I still do some freelance translating on the side of my current job)” and “If there was a feasible option of getting into interpreting I’d also be tempted.”

What Can We Do Better?

In a tick box question, respondents selected the factors that would have led them to stay in the language industry. A more interesting role and better long-term career opportunities topped the list, with more money, and better progression, management and work-life balance also emerging as possible difference-makers.

Participants were also asked what advice and recommendations they would have for employers in the language industry through questions such as “If you could change one thing about the language industry what would it be?” and “What, if anything, could your company could have done differently that would have encouraged you to stay in the language industry?”

Of the respondents who said that there was something their company could have done to retain them (60%), all said it would have involved better career developments or pay.

Things that people hoped to change about the industry at large included:

  • “Better salaries compared to Project Managers in other industries”;
  • “Make its employees feel more valued. The turnover was very high as extra duties were heaped on with no reward”;
  • “Make people more aware of how much work is behind a simple translated document, have respect for others’ job/work”;
  • “More honesty around quality assurance”

As the industry matures with a wider breadth of job roles and shows healthy levels of employment globally, companies must pay attention not to lose key talent to competing industries. Some might argue that LSPs are necessarily bottom heavy and that attrition among the more junior levels of project managers and sales employees is to be expected as it is not possible for everyone to progress. But turnover of staff carries a huge cost – not least for training, recruitment and extra overtime – one that can be driven down by heeding advice and implementing good people management strategies.

Reference: http://bit.ly/2LPiFhS

Court Rules That Free MT Isn’t Enough for Legal Scenarios

Court Rules That Free MT Isn’t Enough for Legal Scenarios

In recent months, we have increasingly heard from enterprise localization groups that their executives are pushing for the adoption of neural machine translation (NMT), driven largely by a very successful public relations campaign from Google that has touted the very real improvements in NMT over the past two years. Unfortunately, some business leaders have seen media coverage and concluded that they no longer need language professionals and can simply replace translators with the “magic” of AI.

Given the way many people have come to treat Google Translate and its competitors as authorities on all matters linguistic, it was really only a matter of time before free, online MT played a role in a court case. Recently, an English-speaking police officer in Kansas City used Google Translate to converse with a Spanish-speaking individual and obtain consent to search his car. In the course of the officer’s search he discovered a large quantity of illegal narcotics. It seemed an open-and-shut case: he had permission to search the vehicle and found the drugs.

But a judge threw out the case: Google Translate rendered the officer’s “Can I search the car?” in Spanish as “¿Puedo buscar el auto?,” which is more along the lines of “Can I look for the car?” The defendant successfully argued that he gave permission only for the officer to look for the car, not look in it. The court ruled that the Google Translate output was not sufficient for consent and tossed the case.

Although legal experts argue that this particular case is unlikely to change things much – police can take additional steps to clarify consent – it points to the danger that comes from relying on MT uncritically and should serve as a caution against uncritical MT boosterism. It won’t slow down the adoption of MT – the economic requirements it fulfills are too compelling – but cases like these should provide a wake-up call for naïve adoption in cases where accuracy matters. NMT may be great when you are willing to ask questions and clarify responses, but you cannot rely upon it for cases where the results can affect life, liberty, or liability… or your bottom line.

The lesson here is not that MT is bad. After all, humans can make similar mistakes. Consider the case of Willie Ramirez, which resulted in a US$71 million judgment against a hospital, centered around a misunderstanding of the Spanish word “intoxicado” – which means “poisoned” rather than “intoxicated” – that left a young baseball star with permanent disability.

The difference is that humans respond to context and can take steps to clarify, while MT by itself does not. It provides a best machine guess at a translation, but takes no responsibility when things go wrong. Google specifically states that it does not provide any sort of warranty that its services will be accurate or usable, and indeed the company could not do so given the way its technology functions. By contrast, a human interpreter who would be liable for getting something wrong will have a strong incentive to make sure that the details are correct. An expert linguist will know what matters in a given context and ensure that the communication reflects it. MT doesn’t care.

Contrary to fears that MT will replace human translators, CSA Research’s examination of the issue shows that MT can augment human translators, making them more efficient and better able to focus on the important details.

Our research shows LSPs that MT accelerates the growth of LSPs that adopt it. LSPs and enterprises alike need to understand the technology, how to work with it, where it applies, and how best to deploy it. Translation buyers need a realistic assessment of what it can and cannot do for them and should work closely with providers to achieve their goals. Like any technology, MT is a tool, and tools used incorrectly can harm their users and those around them, but when applied properly, technology tools deliver real benefits. Just don’t expect NMT to provide you with legal or medical advice and always involve professional linguists when accuracy and message matter.

Reference: http://bit.ly/2mK8ywQ

The Story of WordPress is the Story of Localization

The Story of WordPress is the Story of Localization

Ciklopea published an interview with  Emanuel Blagonić to share his experiences and views on WordPress web development and website localization solutions.

Would you please introduce yourself?

My name is Emanuel Blagonić. I like to say that I am, first and foremost, a father. I am a designer, I design user interfaces and work with small and big companies from Croatia and worldwide. I first encountered WordPress more than 12 years ago when the CMS was very different from what it is now. I have been introducing the benefits of WordPress to the people ever since, which has taken a form of active participation in the Croatian and global WordPress communities over the past few years.

What is the importance of localization in your opinion?

The story of WordPress is the story of localization. The first major success occurred in Japan which was home to the strongest localization community of the world in those days (15 years ago). Localization is the key to success if we want to make something more available to worldwide audiences. The WordPress mission is to democratise publishing, and to do that we need to make the software available to everyone – regardless of their proficiency in foreign languages – and this is where localization is coming to the fore.

What are your experiences with WordPress localization (challenges, solutions, etc.)?

There are two types of localization. One type includes WordPress software localization. WordPress relies on its – at times almost fanatical – worldwide community in that respect. WordPress is actively translated at home, at work, and at the events known as Contributor Days, where many people working in different teams meet to contribute to the WordPress project. More than 500 people attended the Contributor Day recently held in Belgrade as part of the WordCamp Europe conference (currently the largest WordPress conference in the world), who actively contributed to the community throughout the day. One type of contribution is the localization of main software, plugins, themes and more.

Content localization is the second part of the localization story. Content localization is important in terms of target audiences of a specific website. It is important to localize your website for your target audiences to make your content, message or your products and services available to as many people as possible.

What are your experiences with the localization on other CMS platforms?

I don’t really have experience with other CMS platforms so I can’t claim whether localization is implemented better or worse. The basic problem of WordPress – if that can be seen as a problem at all – is that, unlike some other CMS platforms, localization is not an integral part of its installation, but it needs to be “upgraded” through plugins (such as WPML). Although that’s not really an issue, I believe localization could be solved better under WordPress. However, the facts that 30 % of all the world’s websites are powered by WordPress (its share among the CMS platforms has long been larger than 50 %) and that it is the most popular CMS of them all makes the case for WordPress content localization being an important part of your online strategy.

Is localization process affected by website complexity?

It surely is. You can opt for different approaches to localization based on the website “size”, i.e. its complexity. The users most frequently choose WPML as the most professional WordPress localization plugin, and those who do not want to pay for it (WPML is a premium plugin) opt for other solutions.

As always, every solution has its pros and cons, and with very complex websites it is perhaps best to consider a customized solution with each language being a separate WordPress (multisite) installation where content connection will be solved with custom software code.

WPML is the genuine commercial solution that provides a wide range of possibilities to translation agencies who use specific tools, making the localization process faster and smoother.

Is localization something to be considered before or after the development?

Definitely before. Although it is possible to localize a website after it has been published, I believe that having an initial plan of what needs to be done today, tomorrow and the day after tomorrow always pays off. If we have a vision for the next two or three years, in addition to being able to make an easier prediction on the type of content that we need, we will also have a better insight into the localization requirements. Based on that, you will be able to choose a better solution, of course, in collaboration with your web developers.

Why is it important to choose a professional LSP for website localization?

As always, having professional and reliable partners is important. Although we tend to believe that if we can understand and speak, say, English, we can also translate content, we should be aware that a self-service translation (mostly) does not meet the expectations of our audiences on the target markets. If you are targeting British, German, Italian, French, Russian or any other market for that matter, it is important to have a professional translation because your website in most cases serves as your reflection and the place of first contact with your potential clients. Of course, this is something that leaves an impression, so it is important to make the impression you want.

Reference: http://bit.ly/2LAQkvU

Creative Destruction in the Localization Industry

Creative Destruction in the Localization Industry

Excerpts from an article with the same title, written by Ameesh Randeri in Multilingual Magazine.  Ameesh Randeri is part of the localization solutions department at Autodesk and manages the vendor and linguistic quality management functions. He has over 12 years of experience in the localization industry, having worked on both the buyer and seller sides.

Te concept of creative destruction was derived from the works of Karl Marx by economist Joseph Schumpeter. Schumpeter elaborated on the concept in his 1942 book Capitalism, Socialism, and Democracy, where he described creative destruction as the “process of industrial mutation that incessantly revolutionizes the economic structure from within, incessantly destroying the old one, incessantly creating a new one.

What began as a concept of economics started being used broadly across the spectrum to describe breakthrough innovation that requires invention and ingenuity — as well as breaking apart or destroying the previous order. To look for examples of creative destruction, just look around you. Artificial intelligence, machine learning and automation are creating massive efficiency gains and productivity increases, but they are also causing millions to lose jobs. Uber and other ride hailing apps worldwide are revolutionizing transport, but many traditional taxi companies are suffering.

Te process of creative destruction and innovation is accelerating over time. To understand this, we can look at the Schumpeterian (Kondratieff) waves of technological innovation. We are currently in the fifth wave of innovation ushered in by digital networks, the software industry and new media.

Te effects of the digital revolution can be felt across the spectrum. Te localization industry is no exception and is undergoing fast-paced digital disruption. There is a confluence of technology in localization tools and processes that are ushering in major changes.

The localization industry: Drawing parallels from the Industrial Revolution

All of us are familiar with the Industrial Revolution. It commenced in the second half of the 18th century and went on until the mid-19th century. As a result of the Industrial Revolution, we witnessed a transition from hand production methods to machine-based methods and factories that facilitated mass production. It ushered in innovation and urbanization. It was creative destruction at its best. Looking back at the Industrial Revolution, we see that there were inflection points, following which there were massive surges and changes in the industry.

Translation has historically been a human and manual task. A translator looks at the source text and translates it while keeping in mind grammar, style, terminology and several other factors. Te translation throughput is limited by a human’s productivity, which severely
limits the volume of translation and time required. In 1764, James Hargreaves invented the spinning jenny, a machine that enabled an individual to produce multiple spools of
threads simultaneously. Inventor Samuel Compton innovated further and came up with the spinning mule, further improving the process. Next was the mechanization of cloth weaving through the power loom, invented by Edmund Cartwright. These innovators and their inventions completely transformed the textile industry.

For the localization industry, a similar innovation is machine translation (MT). Tough research into MT had been going on for many years, it went mainstream post-2005. Rule-based and statistical MT engines were created, which resulted in drastic productivity increases. However, the quality was nowhere near what a human could produce and hence the MT engines became a supplemental technology, aiding humans and helping them increase productivity.

There was a 30%-60% productivity gain based on the language and engine that was used. There was fear that translators’ roles would diminish. But rather than diminish, their role evolved into post-editing.

The real breakthrough came in 2016 when Google and Microsoft went public with their neural machine translation (NMT) engines. Te quality produced by NMT is not yet flawless, but it seems to be very close to human translation. It can also reproduce some of the finer
nuances of writing style and creativity that were lacking in the rule-based and statistical machine translation engines. NMT is a big step forward in reducing the human footprint in the translation process. It is without a doubt an inflection point and while not perfect yet, it
has the same disruptive potential as the spinning jenny and the power loom. Sharp productivity increases, lower prices and since a machine is behind it, the volumes that can be managed are endless. And hence it renews concerns about whether translators will be needed. It is to the translation industry what the spinning jenny was to textiles, where several manual workers were
replaced by machines.

What history teaches us though is that although there is a loss of jobs based on the existing task or technology, there are newer ones created to support the newer task or technology.

In the steel industry, two inventors charted a new course: Abraham Darby, who created a cheaper, easier method to produce cast iron, using a coke-fueled furnace and Henry Bessemer, who invented the Bessemer process, the first inexpensive process for mass-producing steel. The Bessemer process revolutionized steel manufacturing by decreasing its cost, from £40 per long ton to £6–7 per long ton. Besides the
reduction in cost, there were major increases in speed and the need for labor decreased sharply.

The localization industry is seeing the creation of its own Bessemer process, called continuous localization. Simply explained, it is a fully-connected and automated process where the content creators and developers create source material that is passed for translation in continuous, small chunks. The translated content is continually merged back, facilitating continuous deployment and release. It is an extension of the agile approach and it can be demonstrated with the example of mobile applications where latest updates are continually pushed through to our phones in multiple languages. To facilitate continuous localization, vendor platforms or computer-assisted translation (CAT) tools need to be able to connect to client systems or clients need to provide CAT tool-like interfaces for vendors and their resources to use. The process would flow seamlessly from the developer or content creator creating content to the post-editor doing edits to the machine translated content. The Bessemer process in the steel industry paved the way for large-scale continuous and efficient steel production. Similarly, continuous localization has the potential to pave the way for large-scale continuous and efficient localization enabling companies to localize more, into more languages at lower prices.

There were many other disruptive technologies and processes that led to the Industrial Revolution. For the localization industry as well, there are several other tools and process improvements in play.

Audiovisual localization and interpretation: This is a theme that began evolving in recent years. Players like Microsoft-Skype and Google have made improvements in the text-to-speech, speech-to-text arena. The text to speech has become more human-like though it isn’t there yet. Speech-to-text has improved significantly as well, with the output quality going up and errors reducing. Interpretation is the other area where we see automated solutions springing up. Google’s new headphones are one example of automated interpretation solutions.

Automated terminology extraction: This is one that hasn’t garnered as much attention and focus. While there is consensus that terminology is an important aspect of localization quality, it always seems to be relegated to a lower tier from a technological advancement standpoint. There are several interesting commercial as well as open source solutions that have greatly improved terminology extraction and reduced the false positives. This area could potentially be served by artificial intelligence and machine learning solutions in the future.

Automated quality assurance (QA) checks: QA checks can be categorized into two main areas – functional and linguistic. In terms of functional QA, automations have been around for several years and have vastly improved over time. There is already exploration on applying machine learning and artificial intelligence to functional automations to predict bugs, to create scripts that are self-healing and so on. Linguistic QA on the other hand has seen some automation primarily in the areas of spelling and terminology checks. However, the automation is limited in what it can achieve and does not replace the need for human checks or audits. This is an area that could benefit hugely from artificial intelligence and machine learning.

Local language support using chatbots: Chatbots are fast becoming the first level of customer support for most companies. Most chatbots are still in English. However, we are starting to see chatbots in local languages powered by machine translation engines in the background thus enabling local language support for international customers.

Data (big or small): While data is not a tool, technology or process by itself, it is important to call it out. Data is central to a lot of the technologies and processes mentioned above. Without a good corpus, there is no machine translation. For automated terminology extraction and automated QA checks, the challenge is to have a big enough corpus of data making it possible to train the machine. In addition, metadata becomes critical. Today metadata is important to provide translators with additional contextual information, to ensure higher quality output. In future, metadata will provide the same information to machines – to a machine translation system, to an automated QA check and so on. This highlights the importance of data!

The evolution in localization is nothing but the forces of creative destruction. Each new process/technology is destructing an old way of operating and creating a new way forward. It also means that old jobs are being made redundant while new ones are being created.

How far is this future? Well, the entire process is extremely resource and technology intensive. Many companies will require a lot of time to adopt these practices. This provides the perfect opportunity for sellers to spruce up their offering and provide an automated digital localization solution. Companies with access to abundant resources or funding should be able to achieve this sooner. This is also why a pan-industry open source platform may accelerate this transformation.