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Creativity In Translation|Translator Thoughts

Creative translation

Did you ever think about how translation is creative? Translation can be viewed as a  link between two different languages, mindsets and cultures.

Creative translation associated with a large number of target languages of source text into another language. Creative translation is widely used in the advertisement purposes.

Advertisement consists of concocting attention-grabbing taglines for various products primarily for the marketing purpose. This marketing trick grabs the attention of the customers towards the product.

The task of translating a text into a new reality, and being a medium between two different languages make the translator natural and creative.

Translator not only changes words from one language to another. It is more complicated; sometimes the translator uses entirely distinct words to convey the same meaning.

Sometimes it is not 100% perfect translation, but as long it conveys the meaning it is acceptable to the target audience.

Creative translation

Creative translation can be seen in many ways such as :

1.Linking Different Skills:

Interpreter and Translator can be defined as a medium to interact between two languages and two different persons speaking or writing them by combining different skills.

To translate some documents especially legal content is not really an easy-peasy thing to do. The translator has to tackle numerous kind of problems before getting a good result.

They have to combine the fluency of the language, deep writing skills and a good understanding of the cultural hints of the source and as well as the target audience.

2. Personal Style:

A translator always dips, however, less it might seem but into his/her personal style which again influences the resulting content. Hence, the output can be said, as directly connected to the person who produced it.

If there is two same work of literature or two distinct translators,  they will do the job in a different style. But the outcome is the same as in the original text. This is because the translator has its own form.

A translator has its own words, phrases, and terms those are different from one another. These shall be some of the convincing reasons to prove that a translator has its style.

3.Innovative perception:

Firstly, a translator needs to be an absolute expert in the field that he is in. Secondly, they also have to do an in-depth reading to achieve the essential knowledge.

The more you gain the knowledge, the more you know, create and explore. The translator shall always have his fast presence of mind in order to perceive the words from a language and to replicate the same word in the other language. In other cases, he should be extremely creative in using a different word but which portrays the same meaning from the targeted language.

Anyone who finds better and innovative solution to the given tasks, they become more skilled in one area and quickly resolve the major errors.

4. Copywriting:

Translators provide excellent copywriting assistance as a way to improve and as a simple extension to translation.

They can be considered brilliant copywriters and they can approach the text from the translators’ perspective.

Translators engaging in copywriting services, and their natural ability is much bright and specific.

5. Language Creativity:

As a painter implements colors to paint out their creative mind and like a guitarist who uses his guitar to make his creativity vocal. Similarly, a translator uses their attribute of languages as their tools of creativity.

The translator uses a combination of words, phrases, and languages to voice out their creativity. Translator delivers text that is not only an excellent translation but can also be noted as an interesting document to go through.

6. Outstanding Branding and Marketing Skills:

When it comes to marketing, Translators are proven boom in the market industry.

A creative person can do a great marketing job with the help of the translator.

With their excellent writing skills, they can create a superb tagline to attract customer all over the world.

With the help of their writing, they can create their brand promote it. Translator connects the dots and helps to give his message to the clients.

The skills to translate the services into design, colors, and a brand name is simply admirable.

7. Excellent in other arts:

People who have artistic skills display their talents in multiple techniques. It is quite a shock to know that most of the engagement of the writers and translators in music, fine arts, singing and so on.

This is due to them indulging in creative ideas and understanding the perfect source and translating them into an ideal target.

So, here there shall be an obvious question for you that which of these techniques you think is the best for a Creative translation? I hope to form this article you will get an idea that how a translator uses its creativity.

Artificial Intelligence Can Translate Languages Without Human Interference

Artificial Intelligence

The era of Automatic translation of language has come a long way. This is all because of Neural networks computer algorithms that recognize the inventiveness of the human mind.

However, there is a huge requirement of data to train such networks. Millions of translations from sentence to sentence are required to show how a human would usually do it.

Today, there are two newspapers that show how neural networks can learn to translate without two parallel texts. This astonishing advanced step will ensure that the documents are widely accessible and in several languages.

Artificial Intelligence

Artificial Intelligence Goes Bilingual

Mikel Artetxe, a computer engineer and a scientist at the University of Basque Country revealed that they have a computer which can translate two languages.

Mikel presented his invention by giving an example of a situation when Chinese and Arabic books are given to learn and consequently to translate them. This seems like an impossible task for a normal human being. However, this is now possible. Thanks to Mikel who shows that it is possible for a computer.

A lot of the machine learning works under supervision. That is, say a computer makes a guess and receives the right answer. Then, it instantly adjusts its process accordingly. This method works smoothly when a human teaches the computer to translate popular languages like English and French. As a lot of documents are available in both the languages.

These two new papers focus on another method, that is Unsupervised machine learning. In this method, each of the computers is given out bilingual dictionaries without the help of a human tutor to tell them which of their guesses are correct.

This process is a possibility because in languages there is a lot of similarity between the words that gather around each other. As an example, words like Chair and Table are together in every parallel language.

Methods Used By The New Papers

The new papers use methods which are very similar. They translate on a sentence level. They use a couple of training methods. One is back translation and another is denoising.

In the Back translation, one sentence of a language is barely translated into another language and its translated back to the original language again. If the back-translated sentences are not similar to the original language then the adjustments of the neural networks should be in such a way that from the next time the translation is closer.

Denoising method is kind of similar to Back translation. However, it works in a slightly different manner. Instead of translating from one language to another and vice versa, Denoising adds more noise to a sentence. Adding noise means removing and rearranging the words and translating it back to the original.

These methods together provide more knowledge about the deeper structure of language to the network. There is a little difference between the use of the techniques to translate languages.

The UPV system back translates constantly during the training period. Whereas the other system created by a Facebook computer scientist, Guillaume Lample adds an extra step to the translation process.

Although both the systems encode a language into an abstract language before decoding it back to the original, the Facebook system does it with a slight difference. This system makes sure that the other language is truly abstract or not before the encoding and decoding process.

Artificial Intelligence Rising To Incredible Heights

In addition to the translation of language without many parallel texts, the system methods can help with the translation of common pairing languages like English and French. This could help if the parallel texts are of the same kind, as the newspaper reports, but you want the translation in a new domain such as street slang.

It came as a shock for Di He, a computer scientist in Microsoft, that the computers could learn to translation without the help of a human. Although he also added that this shows that the approach is in the taking place in the right direction.

The Most Important Trends In Translation Technology 2018

translation industry

The translation industry is one of the most important and rapidly growing industries in the world today. This industry is undergoing a massive change in the last decade. With the consumption of over 38 million in the market, this industry further highlights an annual growth rate of 6%.

It is predicted that there will be over 30% growth rate in the translation industry when it comes to jobs. This is the new change that the companies need to get more accustomed to. There is a new change occurring almost every in every passing minute. Hence, the requirement for the businesses to be up to date is on the high. Companies need to be aware that this is a very powerful industry now.

With the rise in the use of technologies, the new technical developments will constantly have an impact on the workings and how we can carry several things out simultaneously. Therefore, companies will need to be updated with all the translation trends and the predictions as well so they remain a step ahead of their competitors in this demanding industry.

New technologies are the major reasons behind the evolution of the translation industry. This article provides a list of the top 5 and most important trending translation technology of 2018.

translation industry

1. Enhancing the Customers’ Experience

A customer’s faith determines how healthy the relationship is between the company and its customers. Today, all the information required is available online. This makes it really tough for the translation companies to stand out among their competitors.

Therefore, companies will be putting more focus on interacting with the customers. This will further add more value to the company. It also makes the client purchasing experience simpler.

2. Improvements in Translation Technology

Today there are several applications available for language translation. Some of the most used translators today are Google Translator, Bing Translator, and Microsoft Translator.

Translating the languages have become an easier task for the companies now. These technologies are set to become even better in 2018. There will be a rise in the requirement for a more integrated and customizable process.

3.The emergence of New Business Models

In the translation industry, the common payment model is paying by the number of words. However, this model could soon see a fall as paying for words may not be the best paying method for the services like Trans-creation and Multimedia.

For an instant, the trans-creation of 5 words for a TV show will take days of work and research. Similarly, for Multimedia, the work of people like Graphic designers and Voice artists cannot be valued merely by the number of words.

4. Rampant growth in Mobile Apps Translation

One of the top translation trends for 2018 is the Mobile Apps Translation. The application developing companies and their developers are constantly attempting to reach the maximum number of audience. It is practiced in order to raise the profit by developing more translation apps in numerous languages.

Mobile App translations were visibly in the rise during 2017 and are expected to continue growing also in the year 2018. A figure shows that there are around 5.7 million applications which facilitate the function of translation available for download in 5 top grossing app stores.

5. Business Intelligence Proving to be a Crucial Tool

Today, more companies look into the factor of how business intelligence tool can help them to make further improvements as their developments. With the advance in technology, just to know about the current state of the project is not going to be enough anymore.

2018 will see more and more people employing predictive tools as a key to examine the local business in the coming future. On a similar note, the customers rely more on the effects of translation figures to assess the rise in the customer satisfaction.

New technologies are simplifying the Translation

Indeed, the advances in the technology are simplifying the translation process. More software companies and developers will develop new translation apps which will provide a better user interface. The translation services will be provided to the customers in a cost-effective manner.


Can Technology Replace Human Interpreters?The Future of Translation Technology

translation industry

Last year, the world witnessed a drastic change in shaping the translation technology. Uncovering the two major Artificial Intelligence systems, which are capable of learning any languages known to humans.

Most of the major companies are already experimenting to make the translation technology better for the online consumers.

Last year, the big e-commerce giant Amazon joined the group by launching Amazon Web Series. The Translate app provides translation for all the languages supported to promote the products and services with ease.

The big corporate giants like Google and Microsoft offering the translation technology for a long time, individually.

At this point do we really need another translation application? Is the technology is improving? Or just the diversifying the option where to get it from?

Translation Technology

One of the In-Demand Services Of 2017 – Translation

According to Global Market research, the translation industry will hit 1.5 billion dollars by the end of 2024.  So, this considered as the good news for translators and also for those who are closely working with translation application.

In a study conducted by the Bureau of Labor Statistics highlights, around 17% of the employment growth for interpreters and translators 2026. As this is becoming the strong need for business organizations to promote business globally.

The growth is considerably faster than other that of other occupations. In light of the fact, companies are also offering more than 10K position on this fast track.

Amazon’s AWS backs up this act of pushing the business growth globally. Business entities are focusing on expanding globally by merging the translation tools and software into a business. However, to reach out to a significant customer database overseas, they need to offer more localized language. Which is beyond expectation at this point for any translation tool.

New Opportunities For Translators

Technology is opening up some new branches for translators. Chinese, German, Russian, Spain, Portugies are some of the major languages impacting the global market. Among others, these languages open a bigger job perspective for the translators.  

On the other hand, it is not unusual to think the translation tools are cutting the edge for human translators. For a fact, they are making the job opportunity.

In spite of technical advancement in the field of Artificial Intelligence, and machine translation, it still needs close human supervision. Close supervision by the professional translators can ensure correct dialect and use of grammar.

Even though machines are using the improved and advanced algorithms, still when it comes to a faceoff, it still can’t beat the human translators.

Sejong Cyber University put three machine translator against a group of human translator into a test. Results appear to be quite disappointing for machines. They had to struggle to live up to the expectations for the creator. Machines are, of course, faster than human translators but they are likely to make mistakes while completing the sentences.

During the building of the machine, it requires a specialist knowledge to minimize this problem. To make this technology accurate, hiring a technical translator should deliver a better end product. With a precise technique, business entities can reach to global customers

Industry Specific Translation Apps Are Coming Out

Machines are not yet entirely accurate when it comes to translating a piece of document and information. They are still making grammatically incorrect sentences, making it less reliable than a human translator. For industry-specific machine translators, it has to be more accurate. For instance, law, medical, education, which is far beyond the capacities of human translators.

To provide accurate information on this type of translation, interpreters should be trained under terminology. While the developers work on the advancement of the technology, to make the technology accurate the human translators will look forward to the global expansion of the business.

AI- Still Waiting For The Revolution


Artificial Intelligence- a term that is recited by everyone alike and usually misunderstood. This is way different from the classical case of the general public not understanding the scientists. The idea of AI- something that rivals our intelligence, not only entertains us but also scares us to the same extent, also distracting us, unfortunately.

Artificial Intelligence

A Little Story

I remember reading a story somewhere about a pregnant woman. Her fetus was diagnosed with Downs syndrome. The ultrasound machine showed some white spots that indicated the presence of the abnormality. She was suggested to go for amniocentesis to be sure if the fetus has the genetic modification. This was a risky test where the chances of a fetus being killed were 1 in 300.

Cutting the Long story short- later, they realized that the analysis was done almost ten years back in the UK. These white spots indicated the deposition of calcium which acted as the predictor of the Down Syndrome. Apparently, the fact was ignored that the machines used today are far advanced with more pixels per square inch. Those white spots are just white noise and not something to be worried about.

The fact of the matter is that the analysis has stayed as they were as the technology is advancing. The problem lies in the time of analysis and the time it is used in. Before we use a data, we must keep in mind where when data came into existence and how relevant it is in today’s time.

The Real face Of Artificial Intelligence

We are still far away from bringing together Humans and computers in such a way that it enhances Human life. While some think this problem comes along with and is subservient to the creation of Artificial Intelligence, others also consider it as the chance to create a new branch of engineering.

The machine learning of past several decades has become AI today. The phrase AI came into existence in the late 1950s for referring to the aspiration of providing software and hardware human-level intelligence. In the 1980s, when the backpropagation algorithm was rediscovered, it brought the ‘AI revolution’. We sure have come a long way since Machine Language and first ambitious use of AI.

Way To Go

The system still has shortcomings and issues like security and privacy. These are not just the only problem, these are challenges. The success in the field of AI is limited right now. Truth be told, we still have a long way to go before we can realize the AI aspirations that could imitate humans. Unfortunately, even a limited success catches the attention of media and hypes it up.

We already depend on the technology quite a lot. But the revolution in the field of AI is still awaited. It is going to be very complex and challenging.

Artificial Intelligence Just Got Smarter- Goes Bilingual


Neural networks have given automatic language transition a new face. It is an algorithm that is inspired by the human brain. They used huge labeled datasets to be trained to do a variety of complex tasks like the human brain that performs only after gaining the knowledge about something.

Now suppose, you were given Chinese and Arabic books and need to learn to translate Chinese into Arabic. Will you be able to do that? No one among us can. But now, the computer can do that.

                                       Artificial Intelligence

The Breakthrough Story

Yes, you heard it right. Two teams of computer scientists have gained success in translating languages with the use of Artificial Intelligence. Both groups, one from Facebook and other from the University of the Basque Country (UPV), independently created techniques through which neural networks can translate languages. Artificial intelligence can do that without using human intervention or a dictionary. It is all about unsupervised machine learning.

However, its bilingual evaluation understudy score came to 15 in both directions. It is lower than that of Google translate which is 40 or Human who can score 50. But, it is way better than word-to-word translation. Isn’t it? And this is just the beginning. No one knows where this road is headed and what surprises it will bring.

The secret is unveiled

When you hear such wonderful and magical things, a question often haunts your brain- how is it done?

The techniques of both the groups first recognize the pattern in each language. They identify commonly paired words like shoe-socks, tree-leaves, table-chair, etc. that are common across the languages.

Once these patterns are recognized, the neural network then links these co-occurrences in both the languages. This develops a bilingual dictionary on the accuracy of the translation, without any human feedback. Then, these dictionaries are used for translating the whole sentences.

It is more like a giant atlas with words for cities. The maps in each language will resemble each other with just different names. All computers do is figure out a way to overlay one map over another and voila, you have a bilingual dictionary ready.

Apart from this technique, neural network uses two more ways- back translation and denoising.

In back translation, a sentence is translated to the required language and then back again to the original language. If there is any discrepancy between the two sentences, neutral networks adjust itself and then tries to make a more accurate translation.

We Taught AI Racial And Gender Biases


Programs like Google Translate has experienced a dramatic hike in the ability of language interpretation in past few years. Thanks to the new machine learning techniques and of course to the numerous online text data. It is on these data that the algorithms can be trained.

Everyday machines are acquiring the human-like abilities of language. Along with it, they are also inheriting the deeply ingrained biases hidden in the patterns of language. AI has been seen exhibiting a striking gender and racial biases. Many studies have proved that AI is biased towards gender and races. Is it really biased?


Is AI Biased Or We Are?

People say that this shows AI is prejudiced and biased. No, it shows we are biased and prejudiced and AI is learning it. Because we are assisting AI in its learning. It is reinforced in AI because algorithms are unequipped in consciously counteracting the learned biases, unlike humans.

Embedded Biases

Machines learn from Word Embedding. This process has transformed the way computers interpret text and speech. This method has successfully helped computers in making sense of the language in past few years.

Word Embedding builds up a mathematical representation of language. The meaning of a word in it is distilled into a series of numbers, called Word Vector and based on which related words and terms words frequently appear together.

For example, in the mathematical language space, words for flowers and pleasantness are clustered closer while words for insects and unpleasantness appear close together. Thus, to AI flower is connected to pleasantness and insect to unpleasantness.

This purely statistical approach has captured the social and cultural context of words differently than a dictionary. Some of these implicit biases in the experiments of human psychology has been captured by these algorithms. Words like female and women became closely associated with arts, humanities, and home while the words male and the man appeared closer to the professions like Math and engineering.