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How to skyrocket your SEO strategy with Artificial Intelligence

Have you ever tried to build a semantic core for a site at least once in your lifetime? Or create a competent content strategy? If the answer is yes, then you probably know how difficult it is, and how much information you need to process and take into account to get the right result. This is a difficult and time-consuming task for a human, but it is a mere trifle for artificial intelligence (AI).

Artificial intelligence and machine learning can not only skyrocket your search engine promotion strategy but also change your entire business strategy as a whole. Let’s find out how it works.

You are probably already using AI even if you don’t know it

Most of the actions that we perform either online or using our smartphones have already been reinforced with artificial intelligence. When we ask Siri to create a new alarm clock or make a Facetime call, AI algorithms begin to work. The same thing happens when we write a search query in the search bar. Google ranking and content delivery algorithms are AI algorithms that work using massive amounts of data. The moment we click the Search button, the smart program starts looking for the best solution for us, taking into account the search query itself, our location, as well as all the personal data that we shared with Google for a long time.

Every time we hear that the content ranking algorithms have changed, this means that Google’s artificial intelligence began to behave a little differently. Of course, we can play games with machines for a long time, trying different strategies and evaluating the results.

But why not use Google’s own techniques in our efforts? Enhanced AI software can cause Google to show your pages more often and to the users whom they really suit. All you need to do is start using these innovations.

Coming up with Killer Headlines

It is a well known fact that the headline of a post makes or breaks the post itself. People won’t click through to a post if the headline is not catchy. Luckily there are a number of good AI-based applications that can help you evaluate the quality of your headlines and applications that can suggest ideas for your headlines  based on your keywords. Here are some of these tools:

* IsItWP Headline Analyzer. This is a good tool that grades your headlines and offers suggestions for improvement
* Sharethrough headline tool. Another tool that grades your healines.
* SEOProcessor Blog Title Generator. This tool generates headline suggestions based on your keywords

IsItWP Headline Analyzer is a great tool that helps you create killer headlines for your web pages

Research Content Ideas

You are most likely familiar with the Hubspot Blog Ideas Generator. This is artificial intelligence in its purest form. It is quite limited in its free version, but there are more advanced tools on the market. They also allow you to get a list of ideas for articles based on several key queries, but the key difference is that these systems are able to analyze a much larger stream of data, including in real-time.

That is, by writing down a few key phrases about your topic, you can get valuable insights about what’s trending now, what users are discussing on social networks, and even get predictions about what will be trending in the near future, and start creating your content based on this data. One such tool which is worthy of mention is Buzzsumo.

Buzzsumo provides content suggestions, keywords, topic-related questions and more.

Suggest Better Keywords

Even with the most advanced tools, searching for keywords and compiling a semantic core for a site is always a headache. If you do not believe it, just ask your SEO specialist. The most important point is not only to collect the right key queries but also to select the queries that your users use. Effective SEO always means a perfect match.

Artificial intelligence algorithms help you find the best matches, taking into account its knowledge of the market, your business, your users, your competitors, and Google algorithms, of course.  SEMrush is one such leading platform and is highly recommended. Their keyword magic tool is worthy of mentioning as well.

Empower Voice Search

58% of consumers have used voice search to find local business information in the last 12 months (BrightLocal)

Voice search has become huge, especially among smartphone users. Since voice search is somewhat different than keyboard search, it requires a different approach to SEO. Firstly, voice search is much richer and longer-tailed than keyboard search. So if someone would type a search for Document Translation Services, in voice search the query would be more like: where can I get the best document translation service or where can I find document translation services near me near me? That is why SEO experts recommend to optimize for voice search by targeting long-tail keywords and optimizing for local search results.

Other SEO recommendations are to write FAQ pages with short questions and answers. And it definitely pays more than ever to get featured in Google with Rich Snippets. Because that is the only result that Google will audibly play back  in a voice search. See an example below.

 

Artificial intelligence can help you find a list of potential questions, and give you additional insights about how you get featured in Google rich snippets.

Optimize for Images Search

Visual search is another trend that will intensify in the years to come. Advanced AI systems already know how to recognize images on their own. Soon, it will become possible to buy a dress that you saw in the celebrity’s profile on Instagram even if you don’t know either the brand or the model. If you have a retail business, you definitely need to bet on this trend. Moreover, you need to make your images searchable, that is, create a separate strategy for visual promotion. Artificial intelligence and machine learning can help here as well.

Personalize Your Content

Users are already starting to get used to personalized content driven by AI. The simplest example is the news feed in Google Chrome when the news is selected for you based on your interests and search queries. You can also use this approach on your site, for example, based on data about what your client is looking for on the network.

Translate Your Pages

Google Translate is another application of AI and machine learning, which, by the way, is evolving very significantly year after year. Yes, machine translation still needs to be verified by the person, but the quality is improving markedly. What does this mean for business? No, this does not mean that you can do without professional translation services. But it does mean that you can start by translating your pages by machine, and then apply for the SEO localization services to add relevant key queries in the target language. And go ahead and conquer foreign target audiences!

Suggest Content Optimization Ideas

In this case, artificial intelligence systems will work as an open-minded analyst. All you need to do is to show the system the material that you want to improve, for example, from an SEO point of view, and get new insights about which keywords you can add or what additional sub-questions to discuss in your article.

At this point, most likely you have a logical question – can AI systems create content from scratch? Well, it is expected that by 2026, the program will be able to write essays for high school and get the highest grades for it. But at the current time, these algorithms are too fresh to rely on them completely.

So, is AI the Future of SEO?

Yes, artificial intelligence is the future of SEO. And not just SEO. This is the future of business, and most likely, this is the future of our life as a whole. This is a progressive process that is already irreversible. Statistics show that more and more companies plan to invest in artificial intelligence technologies for different purposes – from introducing a smarter chatbot on the site to optimizing the production process.

Moreover, artificial intelligence for marketing and business is becoming inseparable from other technologies – mobile communications, virtual and augmented reality. The future of the business will be definitely determined by technology, and it is better to start gradually introducing them today.

Conclusion – Are we there yet?

The algorithms of artificial intelligence and machine learning are very powerful and promising, but still need human control and guidance. For the moment these are assistants, but not substitutes, for technical and creative specialists. Use innovative opportunities for data collection, lightning-fast, and advanced analytics, but never downplay the human contribution to business development.

About the Author

Frank Hamilton is a blogger and translator from Manchester. He is a professional writing expert in such topics as blogging, digital marketing and self-education. He also loves traveling and speaks Spanish, French, German and English.

 

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AI Won’t Replace Human Translators Yet. Here Are 3 Reasons Why

Long past are the days when AI was a story created by Science fiction books and movies. Technological advancements in the field have made Artificial Intelligence a practical and valuable resource for the industry. Today, every industrial sector is integrating machine learning in their operations to improve efficiency and productivity. The applications of AI are far and wide; it has outperformed humans in computing large amounts of data to identify meaningful information, it is vital in the research and discovery of new medicine, efficient inventory management, predictive analysis, and more.

Research suggests that AI will automate repetitive and mundane jobs in the coming decade. AI will take over jobs that don’t require critical thinking and decision making, for example, proofreading, market research, bookkeeping, and administrative tasks. Notable technological companies such as Google and Microsoft are also working hard to automate natural languages so that AI can take over for translators and interpreters.

Despite the breakthroughs in voice search technology, AI is unable to match the human brain when it comes to translation and interpretation. This job is still very much occupied by humans. Why? Here are three reasons.

1. Language Is Subjective

Artificial intelligence is incorporated into tasks that are concerned with objective reality. The technology is based upon mathematical and physical logistics to facilitate different functions with extreme accuracy and efficiency. On the contrary, natural languages were invented by human beings to allow easy communication with each other. There are different branches to these languages, such as vocabulary, grammar, tone, etc. but they are constantly evolving to enable better communication.

Natural languages are nuanced; every language is unique to a place and its culture, which enhances its complexity. Recognizing the fine distinctions between meaning, accent, and subjective meaning is a challenge that automatic translators are yet to overcome. AI is not smart enough to understand word inflictions, slang, the emotion behind words, and nuances in tone and style, etc. AI is methodical, and it inspects everything on strict rules of grammar, whereas natural languages are more fluid.

That’s not the case with human translators. They’re known to be well-versed and experienced in the languages, so they’re able to accurately interpret the ins and outs of the language while also respecting its culture. A machine translator will go for word-to-word translation and look no further; meanwhile, a human translator pays attention to the accent and pronunciation of the words before translating. This positions human translators at a much higher expertise level than a machine translator since they’re unable to detect the distinctions in languages.

2. Big Data Has A Hard Time Handling Jokes

Translating humor to a different language is particularly challenging for humans, but it’s next to impossible for AI technology-based translators and machines. Machine translators are dependent on massive sets of predetermined data that are programmed within their systems. On top of that, the data sets are obtained from official translations of government documentation and other religious passages, which leaves little room for exposure to humor, wordplay, and other casual references. This means that the machine will display a translation that could have a high volume of errors without confessing its mistakes. Naturally, the users might not detect these mistakes either and take those results as accurate text.

3.  There Is A Limit to Bot Translations

Nowadays, automatic speech recognition (ASR) is all the rage with the invention of Siri, Alexa, and other smart technologies. They’re considerably pretty skilled at interpreting live speech, but even these inventions are limited to a constricted set of rules and conditions. This is why ASR programs result in a high error rate during live video conferences as they’re unable to grasp the context and references in the speech and often result in misinterpretation.

A hilarious incident ensued when a tourist facilitation company used AI to translate information about regional attractions from local language to English. Instead of writing that the town is known for Shireen band FTP cable factory, the AI translated Shireen Band as ‘Sweet Closed’ thinking of the Arabic word Shireen which means sweet and the Urdu word band which means closed.

Natural languages are updated continuously, and while human translators recognize the evolution of language, AI does not. Machine translators would require consistent upgrades to learn those new phrases, references, etc. so they can eventually find a suitable translation. Even then, it would be a hard job because AI can’t recognize the ‘humanness’ in natural language.

When a text is written, it consists of a writing style, tone, and a personality that differentiates it from other texts or documents. It can have different elements to it depending on the mood and context behind the passage, whether it’s argumentative, poetic, or persuasive. But during translation, the machine is incapable of detecting these elements.  In such cases, only a professional human translator can depict the accurate meaning of the document and deliver anticipated results that don’t lose the structure and tone of the original text.

The issue behind machine learning and translation is that they can’t evolve at the same pace as natural language, which makes them incapable of keeping up with the changes and concepts of the language. Human translators are flexible; they are capable of understanding human subjectivness and the sentiment behind a text and translate it accurately.

Wrapping Up

Today, AI and machine learning are the rage; sophistication in programming and machine learning algorithms have enabled us to design systems that outperform humans in many avenues. AI is being used to reduce the chance of error in complex industries such as space exploration and medicine. It is also being used to achieve better results and drive increased productivity in everyday industries like business, education, and agriculture.

However, while AI’s contributions are impressive, it is safe to conclude that it cannot replace humans when it comes to subjective fields like translation and interpretation. AI can perform simple translations and understand basic concepts within a predefined data set, but it will be ages before it gets even close to perfection.

About the Author

Nouman provides ghostwriting and copywriting services. His educational background in the technical field and business studies helps him in tackling topics ranging from career and business productivity to web development and digital marketing. He occasionally writes articles for Shireen Inc. You can find him on Linkedin here.

 

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Translation trials: Can AI translators beat humans in business?

Artificial Intelligence (AI) is the next big thing in the world of technology. It is nothing less than a revolution in the field of modern software. As any piece of technology before, AI too has posed certain threats to the traditional industries and setups. One particular threat that we will be discussing today is whether AI translators can take over the human translating business around the world?

AI has taken up a prominent place in the human language translation industry and is predicted to make remarkable achievements in the future. According to market research firm Technavio, AI technology will increase dominance in the global translation market in the coming years. Current trends show that AI will be able to replace as many as 500,000 translators and will be used by thousands of language translating agencies. Moreover, there is historical evidence that if machines do the same amount of work as humans then sophisticated machinery can replace humans.

The Current Scenario of AI Translators

In the current setting, AI translators are seen to be better than Google Translate in the major languages (like German, Italian, French and Spanish). One example of an AI MT system is DeepL, an AI translation system that boasts much better results than Google Translate. However, the big engines like Google are capable of translating many more languages than DeepL. More than 100 languages, out of which 32% are in a conversational mode whereas almost 40% are visual translations.

NMT Systems

A relatively new technology being used is neural machine technology (NMT). The machine produces neural connections from the data provided which is used for language translation. The system is generally easy to work with. It can help you achieve translations which are of the same level as humans, in a less complex environment. Another advantage of using these systems is that you don’t need to provide training as in the case of having human translators. One company that is seen as a rising star in the use of NMT is Lilt.

Will AI Replace Humans?

It may sound like AI can take over the human language translation industry, but there are still several loopholes that will affect the industry in many ways. Probably the biggest challenge that the Artificial Intelligence Industry faces currently is the cultural and emotional gap. No matter how sophisticated the AI machinery is, it is not able to understand the human language of emotions neither is it able to bridge cultural barriers. Another issue that arises when using translators instead of humans is when the context is misinterpreted. A small mistake can change the entire meaning of the sentence.

Therefore, in the coming years, AI would have to be able to adapt towards the emotions, tone of voice, and the context in which the sentence is being said along with the cultural aspects. The AI today functions according to the algorithms and codes which are designed by humans. The algorithms are designed and incorporated in web apps using PHP and MySQL web development services.

Undeniably, it is through human efforts that AI has been able to carry out translations in the first place. Therefore, this technology can’t replace humans any time soon. However, it will reduce the number of professionals working in the human translation industry.

Moreover, it is possible that even if AI does reduce the number of professionals in the human translation industry human could still add value to the industry. They can do this by bridging the gap between the human and the machine. This could ultimately help with precisely interpreting the language regardless of any cultural barrier.

Final Thoughts

It seems that humans will stay play an important role in carrying out translations. For effective communication to take place it is important to keep in view the various aspects that make up a language. A very important part of communication in the context, if the context changes the entire meaning changes of the sentence.

In the present day, machines can’t interpret the languages keeping in view certain aspects. Until then, human professionals will still be considered as the most reliable means of conducting translations.

Author Bio: 

Arsalan Hassan

Arslan Hassan is an electrical engineer with a passion for writing, designing and anything tech-related. His educational background and experience in tech has fueled his passion for writing cutting-edge content. He occasionally writes blog articles for Dynamologic Solutions.

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Summarizing Slatorcon Amsterdam 2019

I love Amsterdam. This was probably my fifth time there. Localization conferences I like a bit less and have not gone to one in years. But my love of Amsterdam outweighed any other consideration and I decided to attend the one day Slatorcon Amsterdam 2019 conference on November 28, 2019 which was produced by Slator. And I am glad for this decision, having found the conference to be very good indeed. If you want more details, please continue reading this post.

Conference Venue

Room view at Andaz Amsterdam, Prinsengracht

The conference venue was excellent. The Andaz Amsterdam, Prinsengracht (a concept by Hyatt) is a lovely hotel situated on one of Amsterdam’s canals. This is a great hotel with beautiful rooms and fantastic service. I recommend this hotel highly.

The format of a one-day conference is a great idea. Having attended some LocWorld conferences which lasted for several days, I liked the quick-and-dirty aspect of this one. The talks were brief (about 20-25 minutes each) so my attention span wasn’t challenged too badly. There was ample time for networking and I can honestly say that I met as many of the 80+ delegates that I wanted to. The talks started at 12:30 so there were 1-2 hours of networking before the conference started. There was another round of networking in the middle and a three hour drinks session when the show wrapped up at 6:20 PM.

Food and Beverages

Networking over snacks at Slatorcon Amsterdam

There was plenty of food and drinks during the networking sessions. The food looked very good and was in high demand by the attendees. I myself can’t attest to the quality of the food since I observe the laws of Kashrut and did not eat anything. The drinks session was well stocked with white/red wine and beer.

Conference Schedule Recap

The talks on the whole were good and here is a brief recap:

Andrew Smart and Dave (with Florian in background)

Andrew Smart got things started as the M.C. of the day and introduced the company that he co-founded, Slator.  I found Andrew to be a very nice man with tons of goodwill and industry insight. Definitely a good guy to know.

Slator’s co-founder Florian Faes then took the stage and gave an impressive overview of the translation and localization industry. He covered the main players, the drivers, the industry verticals and spun his vision of the future of our industry. Strong stuff and very insightful.

Slator co-founder Florian Faes

The next talk was by Jimena Almendares of Intuit who spoke about her company’s foray into Mexico and discussed various aspects of localization of their accounting software. Interesting were the details about the local accounting laws and practices, which made the Mexican localization effort much more than just translating software resource files.  Less interesting were details that had no relevance to the localization business (like how they smuggled in PCs for the Mexican employees who could not buy PCs locally for some reason). As an LSP, I got very limited benefit from this talk.

Andrew Bredenkamp of Acrolinx gave a very interesting talk about Artificial Intelligence and machine learning. Most of his talk was not relevant to the localization industry, but gave valuable insights into the current state of AI and where this technology is heading. I think that 25 minutes was way too little for Andrew and I would have welcomed an in-depth talk of several hours. Who knows, maybe it will happen in another time and space.

Andrew Bredenkamp and Dave

Patrick Prokesch of i5Invest gave an excellent presentation of Mergers and Acquisition (M&A) practices in general and in the localization business specifically. This was a powerful talk as it had very relevant information both for language industry company buyers and sellers. The information he discussed was particularly relevant to many people in the room as over 30% of the delegates were at the CEO level.

Esther Bond of Slator was short-changed so to speak and only had a few minutes due to scheduling issues. She discussed her activities as head of research at Slator. I had the chance to talk with Esther at the drinks session and heard about some of the exciting projects she is working on.

Harmut von Berg of LogMein spoke about the evolution of the 6-person localization team he is heading up. How the team consolidated after several mergers at the corporate level and how they managed to merge various departments in the process. I thought that he started out slow but gradually picked up speed to make a very effective presentation. He then ended with what I thought was a brilliant twist: he outlined some of the challenges that his department is faced with now and invited the conference attendants to propose ideas and help them with these efforts. One of the topics on his list was International SEO, which we will get to in a moment.

Panel on Enterprise and Ecommerce localization

The next part of the conference was the panel on Enterprise and Ecommerce localization. The panel was very good but I thought that the stage was a bit small for a 5-person panel. The panel was chaired by Slator’s Florian Faes. The panel members were Andrea Guisado Muñoz of Kayak, Vinicius Britto of Bose, Alvaro (Al) Villalvilla Merelo of Nike and Balázs Benedek of Easyling.

Florian got the panel started by discussing how large multinational companies approach the topic of international SEO. This topic seemed to energize the floor and several people had followup questions and comments. The consensus was that this is a very important issue. After all, what good is a localized website if it is not visible on the search engines? Andrea from Kayak said that her team worked with the internal SEO team to provide language support, but that the responsibility was with the SEO team. Vinicius of Bose and Al of Nike also seemed to indicate that this was not a top priority for their departments. Clearly, this is an an issue which requires close collaboration between localization and SEO teams. But ultimately, localization departments are not focused on this activity.

Another topic discussed in the panel was the use of MT in the localization work process. Clearly MT is being adopted and looked at by all of the large multinational companies. But the consensus on the panel was that this adaptation was in the early stages and did not yet go mainstream. My own thoughts on this are clear and it is my feeling that MT will not replace human translation in our lifetime.

I particularly enjoyed hearing Vinicius Britto (Bose) view on the customer-LSP relationship. LSPs should be solution-oriented. Customers should never have to chase the LSP and wait for the results to happen.  I liked this no-nonsense approach.

The penultimate speaker was Michal Antczak of Paypal. I was a bit confused at a comment that Michal made at the start of his talk, that the views he is expressing are his own and are not those of Paypal. Nevertheless, Michal gave an interesting, somewhat tongue-in-cheek presentation about the relationship between LSPs and their customers.

Dave with Yaron Kaufman and Ishai Givoni of One Hour Translation

The final talk was given by Yaron Kaufman of One Hour Translation. This was an effective talk on the selective use of NMT (Neural MT). Yaron made a compelling argument about the benefits of using NMT in a production environment and how companies can save between 30 and 70% of their translation costs. Yaron provided some metrics that supported his claim and made this workflow sound very real and feasible. What I did gather between the lines is that this approach is geared towards clients with millions of translation dollars in the their budget. One statement by Yaron that I found interesting (even as I disagree with it): MT will eventually, one day take over human translators. When? That Yaron could not predict.

Drinks and After Party

Dante Kitchen and Bar in Amsterdam

As I mentioned previously, there was a two hour drinks and networking session at the close of the conference. This was a very cool session which ended up lasting well over three hours. After so many talks and networking, we all deserved a relaxing drink. At about 9:30 PM the party relocated to Dante Kitchen and Bar which was a short 5 minute stroll from the Andaz. Did I say cool? Indeed it was. Unfortunately for me I had to cut out quickly and prepare for my early morning flight.

My networking experience

I met with a good number of the conference attendees. My own estimation of the breakdown: about 30% were LSPs, 30% were customers who buy localization services, 20% were tool vendors and the remaining percent were financial people and industry observers/consultants. One thing that stood out in my mind was the focus on website localization. I counted at least four vendors that sell website localization connectors-the magic software boxes that connect between a CMS and translation providers.

Special mentions:

Josef Kubovsky is an industry consultant who invited me to visit him in Prague. I actually think I may take him up on his offer as we share numerous professional, personal and cultural interests.

I connected in a meaningful way with Balazc and Peter Farago of Smartling due to the Hungarian connection (my Mother was born in Budapest and Hungarian was my first language as a baby). We promised to set up a video conference soon to review their innovative website localization proxy software.

Lucy Taylor of Bayer had some interesting things to say about the life of a British expat living in Germany and about her work for the pharmaceutical giant. Lucy agreed with the idea that MT would replace human translators, at least for some tasks (like email and internal communications for example).

I enjoyed talking and drinking beers with Andrew Hickson of Ludejo BV, a Netherlands-based translation company. He gave me some interesting facts about life in Holland and the state of the localization industry in that country.

Summing up

Amsterdam and Slatorcon were a great mix. I really hope that Slator does this in Amsterdam again real soon.

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3 Ways Data Analytics is Set to Revolutionize Translation

As the rate of digitization increases, data has become a very important currency in the business world.

In fact, business and technology advisor Bernard Marr explains that we produce 2.5 quintillion bytes of data on a daily basis — a number which has probably increased further since 2018. We generate this veritable mountain of data with our internet, social media, and smart technology usage, and even though just a portion of this data is harnessed for critical analysis, it’s still enough to power an entire sector. Maryville University’s look at the business data analytics industry reveals that the market is set to be worth $95 billion in the US and a whopping $203 billion worldwide by next year. This is bolstered by the rise in quality and quantity of data collected for businesses, which is expected to reach an 180 trillion gigabytes annually by 2025.

In the right hands, big data analytics has the power to change many, if not all industries. Some current real-world uses include the ability to detect diseases early, improve cybersecurity, and optimize campaigns. Considering that internet users and consumers don’t just speak one language, translation for different channels is an important element in collecting and analyzing data. But the question now is: how will translation continue to be shaped by data analytics and related technologies, such artificial intelligence (AI) and machine translation (MT)?

Redistributing workload

The entrance of AI and data analytics into the translation industry won’t signal the end of human translators. Rather, it will free up them up to focus on more complex tasks that require human cognizance and flair. GTS Translation Services previously outlined different kinds of work that can’t be successfully done by MT just yet — namely official documents, literary work, and scanned images or PDFs. These are the kinds of translation jobs that human translators can focus on while MT can take on lower-tier responsibilities, such as working on navigational tools. Another example is in the use of AI as chatbots in customer support. The speed in which they can translate allows them to respond to consumers almost instantaneously, which is a big plus. Humans, on the other hand, can focus on translating more valuable content like contracts, where language accuracy is critical.

‘AI-powered, human-refined’ quality

That said, one of the biggest criticisms against MT is that it too often lacks accuracy when it comes to more complex material. We’ve all seen how tools like Google Translate fumble with winding sentences — not to mention that it sounds awkward or too formal, which doesn’t fit well in different cultural contexts. A Lisbon-based startup, Unbabel, has come up with a logical solution to this ongoing problem, which is to combine the power of AI with the skill level of humans. To date, Unbabel employs 55,000 human translators, who work to “refine” translated texts that first go through their translation engines. This ensures the native and subjective quality of language that fits within certain contexts, while also being delivered at faster speeds.

Speech-to-speech translation

So far, only human translators have shown success in speech-to-speech translation. One common example is the Q&A portion of international beauty pageants, where a professional has to translate a judge’s question to the contestant’s native tongue and her answer back to English. This type of instant speech-to-speech translation is essentially the goal of the Chinese tech company Baidu with their unveiling of an AI-powered translation tool last October. Baidu’s Simultaneous Translation and Anticipation and Controllable Latency (STACL) can translate speech from one language to another to allow for smooth conversation between people using different languages. However, the analytics tool can only translate between Chinese, English, and German currently. But with further research and development, imagine what this can do for businesses, academics, or the travel industry when the tool gets more refined in the future.

It’s certainly a very exciting time to be in the translation industry. Human translators can rest assured that they won’t be replaced by software or robots anytime soon. However, there’s a lot more data to collect, store, and analyze in the future that can continue enhancing machine translation and change the industry forever.

Technology Update created by Joni Bithell for gts-translation.com