Tag: Machine Translation

Summary of 2019: Will Translation Extinct as a Profession?

Summary of 2019: Will Translation Extinct as a Profession?

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What comes to your mind when you hear “Machine Translation”? Do you feel the end coming? Do you think about the end of translation as a profession? Do you imagine yourself jobless after the machine has taken over?

 Advancements in technology, artificial intelligence, and machine learning are creating a competition and a challenge, where the workforce needs to be more intelligent, aware and understanding of the progressions being made to be steps ahead.

 The output of the neural machine translation (NMT) is getting better and better. However, the involvement of skilled human translators is indispensable to safeguard quality. At the moment, there’s a lack of trained post-editors!

 In recent years, post-editing skills have become much more of an asset and sometimes a requirement for translators working in the language industry. Machine Translation has grown considerably in popularity, and the demand for post-editing services has grown in line with it.

 Professional translators are at a disadvantage in that they must make certain to remain updated with the latest technologies. This article offers some tips for translators to keep pace with continuously updating technologies in the workplace, and to help them adapt to technological improvements in the translation process and to changing market needs.

Get to know the MT standards, key terms and concepts related to machine translation and post-editing:

Before working on a post-editing job, you should ensure whether the task is Full post-editing or Light post-editing.

  • Full post-editing:

 Human-like publishable quality (same, as if no MT is used).

The goal of full post-editing is to make the most of the usable parts of the MT text; and at the same time, to make the translation linguistically correct, stylistically elevated, terminologically accurate, and consistent.

  • Light post-editing:

Making the text at an understandable level of translation (making the most of the MT, focusing on speed over quality).

The goal of light post-editing is to make the MT text understandable and adherent to client’s specific requirements concerning the quality of certain elements of the text, e.g.: the client may ask to make sure that product names are left untranslated, or always capitalized, etc.

Consider MT suggestions in CAT tools, when post-editing a project which involves MT:

Usually, the clients provide pre-translated files, in most cases, any matches above 70-75% come from the TM(s), and are handled as in any project, but anything below a 70-75% match is machine-translated content and requires post-editing. If there is no existing TM leverage, the whole text may be machine translated. Post-editors can choose whether to opt for the MT match, a lower TM fuzzy match, or come up with their own translation, but the goal of post-editing is to identify usable parts of MT text and build around these rather than ignore MT suggestions completely and translate from scratch.

Get to know post-editing speed:

The speed a translator can carry out post-editing is directly linked to the quality of the MT output and the post-editor’s experience. A translator may be expected to process 2500-3K words a day, instead of the standard 2K words, provided a MT engine is well trained and produces good quality output.

Get to know the difference between Post-editing & Translating:

Post-editing is a very different process from translation, while translating a text form scratch requires reading the source segment, then translating it. But post-editing requires

  • reading the target segment (raw MT).
  • reading the source segment.
  • asking yourself whether the meaning is the same (if you spend 2 seconds looking at an MT segment, and see that you cannot easily edit it to produce a well-flowing translation, discard it and translate it from scratch or use a lower fuzzy match from the TM, instead.)
  • asking yourself whether the existing mistakes really need to be fixed, or if you are wasting your time on preferential changes.
  • editing raw MT, if required, or starting the translation from scratch (Use the MT as a source of inspiration when looking for the correct translation and pick out bits of the sentence to reuse rather than trying to keep as much of the sentence as possible.)

Get to know common errors made by post-editors:

Below is a list of common errors made by post-editors:

  • Unedited TM fuzzy matches
  • Inconsistently translated terms
  • Translated Do Not Translate Words (DNTs)
  • Unnoticed untranslated words, omitted words, added words
  • Unattended mistranslations
  • Acronyms incorrectly rendered in target
  • Grammar mistakes
  • Under-edited content (Always read through the translation before submitting it. Machine translated content includes false friends and spacing issues – take it for granted and be vigilant. Set QA settings to pick up typos, duplicate words, and trailing spaces. Watch out for term consistency. Usually, the content you are post-editing should be of the same high quality as human translation.)
  • Over-edited content: (Avoid introducing preferential changes – you are risking introducing inconsistent translations and wasting your time. Just follow client-specific instructions and consult project’s TM and TB)

Track the time spent on post-editing:

Make sure to track the time spent on post-editing, and to provide feedback on MT output (especially if you are working on a large MT project).

Get to know the prices of the service you are providing:

If you want to set your own rate: work out how many words you can translate in an hour with the aid of machine translation, then multiply that by your usual per-word rate to get the per-hour rate that you should aim for.

So, for example, if you can translate 300 words per hour without machine translation, and 500 words with MT, and your rate is €0.09 per word, then you should charge €45.00 per hour for PEMT. The fact that you can translate only 300 words per hour without machine translation is not really relevant.

If you want to know what is the minimum offer to accept for PEMT, well, just think of your usual per-hour rate.

If you are a machine translation post editor, share your experience with us. And if you want to be a certified machine translation post editor, you can ask for your language course from here.

Written by Sayed Elattar, Senior Translator and certified MTPE.

Researchers Propose New Way to Detect Machine Translation — Maybe Google Could Use It

Researchers Propose New Way to Detect Machine Translation — Maybe Google Could Use It

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Most machine translation (MT) may still need a human touch before being deemed usable in a professional context. But, even without it, it is becoming less easy to distinguish human writing from machine-generated text.

Yet these gains have one drawback: It is now easier for MT to be abused for malicious purposes, such as plagiarism and fake reviews.

Even Google is having trouble keeping up. In a 2018 Google Webmasters Hangouts session, Senior Webmaster Trends Analyst John Mueller told participants it was possible that some machine translated content had become fluent enough to fool Google’s own ranking algorithms.

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Automatic post-editing for machine translation: a look at the future

Automatic post-editing for machine translation: a look at the future

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Automatic post-editing (APE) is the task of correcting errors in a machine-translated text. Its present and future hence depend on the quality of machine translation (MT) output: poor MT leaves plenty of room for APE; human-level MT does not need APE at all. However, in terms of data and skills required for training competitive models, good MT has a cost that not everyone can afford. To shed light on the future of APE, this post summarizes recent advancements in APE technology, trying to address the question: “At what cost on the MT side will APE become useless?”.

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Wanna Be a Certified Machine Translation Post-Editor/ Project Manger

Wanna Be a Certified Machine Translation Post-Editor/ Project Manger

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Machine Translation Post Editing Courses From Transparent Campus.

Transparent Campus is a learning community developed by Transparent. It is developed to help bridge the gap between theory and practice in the localization industry.  It contains self-paced online courses, webinars, and interactive forums. All courses are customized to the learner’s role, providing the learner with the quizzes and assignments to enhance their understanding and knowledge. After the learner completes the course, they will remain enrolled to receive any updates, news, or webinars related to the course material. 

In the MTPE Skills Category:

  • MTPE Crash Course

Target Audience: Linguists

Duration: 1 Hour

Course Overview: This course is designed as a crash course for linguists. It equips linguists with the know-how to start working on MTPE related tasks. This course focuses on the main MTPE tasks (MT evaluation, light MTPE, and full MTPE). It provides learners with the needed skills along with a simple overview on the MT world and the difference between over-editing and under-editing. 

Certificate: Learner will be awarded a certificate of completion after successfully completing the final quiz with a pass grade.

  • How to Manage MTPE Projects?

Target Audience: All roles involved in handling MTPE projects, i.e. sales, account managers, project managers, and vendor managers. 

Duration: 2 Hours

Course Overview: This course is a journey into the Machine Translation (MT) world, that is rapidly affecting the translation market. During this journey, the learner will delve into how MT works and the history of MT engines. The learner will be equipped with all the necessary skills, along with tips and tricks, to know how to successfully manage MTPE projects and how to choose qualified linguists. It consists of four modules. Each module contains one or more than one quiz.

Certificate: Learner will be awarded a certificate of completion after successfully completing ALL quizzes with a pass grade.

  • MTPE Basics and Best Practices (Generic)

Target Audience: All linguists. 

Duration: 1.5 Hours

Course Overview: This course is a journey into the Machine Translation (MT) world, that is rapidly affecting the translation market. During this journey, the learner will delve into how MT works and the history of MT engines. The learner will be equipped with all the necessary skills, along with tips and tricks, to know how to evaluate and post edit MT output. It consists of four modules. Each module contains one or more than one quiz. All course quizzes are especially designed for this course, and not language specific.

Certificate: Learner will be awarded a certificate of completion after successfully completing ALL quizzes with a pass grade.

  • MTPE Basics and Best Practices (English – Arabic) 
  • MTPE Basics and Best Practices (English – Farsi)
  • MTPE Basics and Best Practices (English – Indonesian)
  • MTPE Basics and Best Practices (English – Thai)
  • MTPE Basics and Best Practices (English – Malay)
  • MTPE Basics and Best Practices (English – Vietnamese)
  • MTPE Basics and Best Practices (English – Japanese)
  • MTPE Basics and Best Practices (English – Turkish)
  • MTPE Basics and Best Practices (English – Polish)

           Target Audience: Linguists work in this language pair. 

Duration: 3 Hours

Course Overview: This course is a journey into the Machine Translation (MT) world, that is rapidly affecting the translation market. During this journey, the learner will delve into how MT works and the history of MT engines. The learner will be equipped with all the necessary skills, along with tips and tricks, to know how to evaluate and post edit MT output. It consists of four modules. Each module contains one or more than one quiz. All course quizzes are especially designed for this course, and will be assessed by native senior linguists. 

Certificate: Learner will be awarded a certificate of completion after successfully completing ALL quizzes with a pass grade.

Machine Translation vs. Machine Translation Plus Post-Editing

Machine Translation vs. Machine Translation Plus Post-Editing

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Any business with an international presence needs top-notch translation services. To make sure you’re communicating effectively with the global market, you need to know that you have accurate, high-quality translations for everything from your website to the digital chatbots that provide customer service.

In a world that continues to churn out more and more content, how can you translate both efficiently and effectively? As machine translation technology continues to improve, your company could find itself facing a number of options–and trying to juggle a trifold need for speed, quality, and cost-effectiveness.

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The Global Data Explosion in the Legal Industry

The Global Data Explosion in the Legal Industry

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As we consider and look at the various forces impacting the legal industry today, we see several ongoing trends which are increasingly demanding more attention from both inside and outside counsel. These forces are:
  • The Digital Data Momentum
  • Increasing Concern for Data Security
  • The Growing Importance of Information Governance
  • Increasing Globalization

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What makes SDL Machine Translation “state-of-the-art”?

What makes SDL Machine Translation “state-of-the-art”?

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SDL Machine Translation is an enterprise-grade solution for those looking to apply the latest in neural machine translation to automatically translate content. With over 20 years of experience, SDL has used the latest advances in the field of artificial intelligence to create a solution that helps organizations break the language barriers for content-intensive processes securely, at scale.

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Secure Machine Translation Minimizes Business Risks for USD 10B Technology Company

Secure Machine Translation Minimizes Business Risks for USD 10B Technology Company

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Even before the rise of neural networks, machine translation (MT) has played a significant role for multinational companies, and not just for customer-facing content.

Global companies need to communicate effectively in the native languages of not just their customers but also their employees and partners. This was the problem faced by a large publicly traded global technology company nearly a decade ago.

The company revenues register over USD 10bn with an operational footprint across 30 countries serving 100,000 customers.

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Ethics in Machine Translation [Podcast]

Ethics in Machine Translation [Podcast]

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We’re in a localization and globalization market now where more words are translated every day through machine translation than what was translated in the entire human language corpus in the past.

Not only does such a massive amount of machine translation radically change the role of human translators, it also creates a whole new range of issues that impact the translation and globalization paradigm itself.

And one of the most important issues is ethics.

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MT Isn’t Good For Languages, But..

MT Isn’t Good For Languages, But..

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In a Sci-Fi movie we all know, there is the machine invention merging in to fulfill a certain demand and a great need covering all the routine and dangerous work. But, there is this end; that we all know by heart as well, the machine evolves and revolts against the maker and works for the maker’s destruction. This shows us the double edged weapon that the machine has. In this article we will reflect these edges: pros and cons, of the machine translation.

The machine has been always a great tool in saving time and money for the sake of exerting the effort to enhance it to produce a better quality. Luckily, we have achieved this, and the machine translation has saved a lot of time translating repetitive content such as the financial field that is full of numbers and the technical content that is full of saved terminology,…etc. Machine translation also grants accuracy translating such content, where no complex structure or ambiguity surrounds the content. It also translates fast, which means less time; and in a world where time means money; this is the best to rely on.

Such applications also evolved to translate images and signs on the spot. Imagine you’re lost in a country you don’t speak its language! No one to understand, no one to ask!

If a programmer or a developer wants to make his application or software or even a website to be used in the whole world, what would he do? Get translators from all the whole world and pay them and get broke before he even takes off?

Machine translation is the answer here as well, as it will be of a great help to this programmer because such a repetitive content will can be translated in a good quality.

On the other hand, the climax of the movie emerges. And we come to the question: does it scheme to destroy the translation profession and the death of the language?

Did it prove high quality in the artistic translation? No, why?

This is due some factors, which are:

  • Perplexity

Language is an evolving living entity. One of the language schools measured the elevation of a language by its ability to complicate. The more complicated the structure and the diction, the higher this language.

Unfortunately, machine translation lacks the ability to deal or understand such complication. This, by turn lead us to the length ratio.

  • Length Ratio

After much trainings and tests to the machine translation followed by evaluation, it appears that the produced is more of chopped sentences, cut off, simple, and normalized affected by the source. This also relates to the language complication; consequently, it defies the language elevation and richness. And speaking of richness, we go to

  • Lexical Density

According to MacMillan Dictionary, it is: “the proportion of content words to function words in a text. The higher the proportion of content words, the greater the lexical density”.

Machine translation is effective at these types of texts that don’t really have many of content words, and it gets sometimes lost the more content words existed. This also applies to the diverse significant word in a translated text, which adds to the richness and the uniqueness of the language. How does the machine translation work with this?

The Machine works with the most frequent words, to keep the text consistent; which threatens the less frequent words with death and oblivion.

However, don’t get disappointed dear linguist, there is this MT Summit that gets to be held globally every 2 years, and regionally every year. They discuss such issues and they try to find solutions for it based on research papers and tests with evaluations. Furthermore, we have you to post-edit these translations, creatively. Machine translation will never replace you, it’s just you who will upgrade and drench yourself more in your language linguistics.

Here, we reach a conclusion that tells us that machine translation is not scheming to the linguists death, unless they allowed, for sure. Nevertheless, it might affect the language.

You do what you got to do.