What is Machine Translation?
Translation services, for the longest, have been a difficult task requiring skilled, schooled translators. For example, a linguist must go through a huge volume of text and provide a precise translation for a project. However, with the advent of machine translation (MT), businesses now have a dependable alternative to human translation services.
Machine translation has gone beyond simple word-for-word translation. Using artificial intelligence (AI), machine translation software can now communicate the full meaning of the original text in the wanted language. But is machine translation really that good? That's what we're about to find out today.
What is Machine Translation?
Simply put, machine translation is the use of a computer program to translate a text from one language to another. The program does this using grammatical patterns, learning algorithms, and databases of preexisting. Using a translation machine, a user can have access to large quantities of translated text in a short amount of time.
In machine translation, the original text is called "source language," and the language you want to translate into is the "target language." The machine translation process actually has only two steps:
Step #1: Take the source language and decode its meaning.
Step #2: Encoding that meaning into the target language.
While the technology has been around for a while - more on that a little later - it has only recently become accurate enough to be used in a professional setting. Today, Machine Learning reportedly accounts for nearly two-thirds of global translation revenue. There's an increased demand for translation and language services in the following sectors:
- Website translations
- Healthcare translations
- Finance translations
- Legal translations
- Manufacturing translations
- Marketing/advertising translations
With its speed and accuracy, machine translation has become an increasingly popular choice for businesses looking to translate their content cost-effectively. But things weren't always like that.
Short History of Machine Translation
The origins of machine translation can be traced back to the 9th century and the work of Al-Kindi, an Arabic cryptographer who developed the first known technique for systematic translation.
The idea of using digital machines for translation didn't become popular until the late 1940s when American mathematician Warren Weaver proposed using computers to translate texts.
It wasn't until 1954 that the first successful machine translation was carried out when IBM developed its first publicly available system. This machine translated words and phrases from one language to another.
By the 1960s, SYSTRAN, a machine translation system, was developed. Xerox used it to translate technical manuals. The system gave basic but useful translations. However, the first commercial of the system happened in 1988 when the French Postal Service used the technology to translate documents for a fee.
Once we reached the 2000s, machine translation was further improved with developments such as statistical machine translation (SMT). Finally, in 2006, Google launched its Translate service and made the technology free for everyone with an Internet connection.
Types of Machine Translation
Fast forward to today, and we have hundreds of machine translation software solutions available. In addition, giants like Google, Amazon, and Microsoft have their services. Plus, specialized services like Bureau Works offer machine translation and automation to companies of all sizes and industries.
Why are there so many machine translation services? Well, that's because the need for large-volume translation has never been higher. According to Moz, more than half of all Google queries aren't made in English. So, to help meet this demand, machine translation services have popped up all over the web.
Despite the number of services out there, all of them use one of the four approaches to translation:
1. Rule-Based Machine Translation (RMT)
As the name implies, the rule-based machine translation (RMT) approach to works by a set of rules. First, language experts developed linguistic and bilingual rules for specific niches and industries. Then, the machines use these rules to translate specific content as accurately as possible. The process has two steps:
- Step #1: The software parses the source text to create a transitional representation of it.
- Step #2: Then, it converts the representation into the target language, using the rules above as a reference.
Rule-based machine translation (RMT) can customize your translation for a certain topic or industry. That ensures that the quality of your translation remains as high as possible.
On the other hand, if the source text uses certain words and phrases that aren't referenced in the rulebook, the translation can be way off. The only way to combat this is to keep the rulebooks up-to-date manually.
2. Statistical Machine Translation (SMT)
Some systems don't need to rely on grammatical rules to accurately translate one language into another. Instead, they learn how to translate by crunching through huge amounts of data and getting the best translation for each sentence.
In statistical machine translation (SMT), systems go through tons and tons of human translations to look for statistical patterns. Once the system identifies certain patterns, it makes intelligent guesses when asked to translate a new text.
The translation predictions are based on the statistical likelihood that a certain word or phrase is used in a certain context.
A sub-category of statistical machine translation (SMT) is syntax-based machine translation. The system uses a set of grammatical rules to translate syntactic units. What does that mean? It analyzes single sentences to incorporate the source language's grammar into the translated text.
Of course, the statistical machine translation isn't perfect by any means. It needs millions of words to process language properly. Without enough data, the statistical translation models may make mistakes.
3. Neural Machine Translation (NMT)
At the dawn of artificial intelligence (AI), developers developed a new way of translating texts. Neural machine translation (NMT) uses AI to learn and translate a language as naturally as possible. Using a specific machine translation technology called neural machine translation networks constantly improves its knowledge and accuracy of the language.
Instead of translating single words, neural machine translation processes (NMT) entire sentences. Then, the data passes through several nudes to generate an output. The human brain structure inspired the NMT module, and the system uses concepts like deep learning to become more accurate.
Unlike other methods, this machine learning software always looks at the input sentence as a whole when coming up with a translation. As a result, neural machine translation doesn't have the limitations of other methods, which is why it often produces more accurate results than RMT or SMT.
With new natural language processing methods being developed, we're just starting to see the potential of this technology. According to Meta research, convolutional neural machine translation networks in development have the "potential to scale translation and cover more than 6,500 languages."
4. Hybrid Machine Translation (HMT)
The fourth and final approach to translation combines at least two of the previously-mentioned machine translation systems into a single piece of software. The approach is used to improve the effectiveness of a single translation method and ensure the best results.
For instance, a system might use a combination of SMT and RMT to leverage the rules from the first to add some structure to the translated text. Conversely, it can use the ladder to make the translated text sound more natural and native.
What is Computer-Assisted Translation?
One phrase you often hear when talking about machine translation is computer-assisted translation, or CAT for short. While their history is interrelated at certain points, CAT and TM are two different methodologies. A computer-assisted translation machine allows you to automate various translation-related tasks like managing, editing, and storing translations.
How does this translation work? The user inputs text into software, which decides it into phrases, sentences, and paragraphs. The tool then saves each separate segment into its database. That allows it to speed up the translation process and ensure high levels of accuracy.
What are some of the best Computer-Assisted Translation tools we have? They include the following:
- Bureau Works - A cloud-based translation management system that leverages human translators and artificial intelligence to give users a fully automated language service. It provides automated translation services to companies like Harley-Davidson, Zendesk, and Uber.
- Crowdin - A cloud-based machine translation software, Crowdin is ideal for tech companies of all sizes. The machine translation software allows users to localize documentation, websites, apps, and even full software suits.
- Lokalise - Possibly the fastest-growing CAT system on the market. The clear user interface has helped thousands of companies on all continents localize their content, improve their translations, and manage their teams.
- SDL Trados - The cloud-based CAT tool is suitable for both freelancers and large teams. It includes built-in features to help manage complex projects, confirm translations, and monitor customer feedback.
- Phrase Strings - Used by companies like Volkswagen, Uber, and Shopify, to name a few, Phrase Strings is a powerful translation system. It supports more than 500 languages, 50 file types, as well as 30 machine translation engines.
Now that you know the difference between MT and CAT tools, let's get back to our main topic. Now, who is machine translation for? Is it simply for translators and translation companies? Or do other industries have something to gain from it as well?
Many different fields require translation services. Here are a couple of use cases for machine translation:
Some 56% of companies worldwide allow remote work. Many of these companies have workers in different countries and even on different continents. While a majority of these workers speak English, language skills vary from person to person. Some workers don't understand formal workplace language.
With machine translation, the language barrier can be lowered or completely eliminated in the workplace. An employee can quickly get a translation of a document, presentation, or company bulletin and save time organizing a meeting with an interpreter.
Besides employees, company stakeholders and partners often aren't fluent in English. A company can use machine translation to ensure global partners can read all important documents and memos.
What's more, even potential customers can benefit from machine translation. It's been estimated that 75% of global consumers don't speak fluent English. With machine translation, businesses can create a seamless customer experience and attract more customers from different countries.
Did you know that an average company possesses and manages nearly 163 TB of data? Processing millions of user-generated data points can be a time-consuming challenge. With machine translation, companies can quickly and automatically translate huge data volumes in a short period of time.
From comments on social media to customer feedback, machine translation can help companies process customer data. Analyzing these data points can provide insights that allow companies to make educated, actionable decisions.
You already know how valuable customer service is. Roughly nine out of 10 buyers are willing to stop working with a company if their customer service agents and efforts aren't up to par. Machine translation allows companies to interact with people all over the globe, no matter their language.
From accurately translating customer requests to increasing the scale of live chat, companies can provide customer responses faster and in customers’ native tongues. That allows the companies to improve their customer service rates without hiring more people in the process.
With customers and employees located in different countries, legal departments often need translators to manage their documentation. In addition to employee contracts, companies often need to translate meeting minutes, special agreements, and other documents.
Besides translating casual and simple documents, machine translation is great for translating documents in different languages. Machine translation technology does this quickly and quite accurately, ensuring lawyers don't miss any important details and protect their companies.
Benefits of Machine Translation
So far, you've realized that machine translation tools are clearly useful for many different organizations in many different industries. But how do you know if the machine translation technology is right for your business?
Although some things are better left to human translators, a wide array of jobs would benefit greatly from artificial intelligence. Here are some of the biggest benefits of machine translation:
Volume at High Speed
When it comes to translation, speed plays a large part. Whether you're running an enterprise or a small, ten-man operation, you need to ensure that the translations you're providing are accurate and timely.
Machine translation is great at doing just that - quickly translating huge volumes of data. An average human translator can translate up to 6 words per minute, while machine language translation software can do up to 30 words per minute.
For decades, business translation has been one of the biggest expenses a company could have. Even now, experienced translators often dictate high per-word prices that are not suitable for smaller organizations.
Fortunately, machine translation tools can drastically reduce your translation costs. According to some studies, machine translation can cost up to 1,000% less than traditional human translators.
Furthermore, you don't need to hire an entire team of translators when using Machine Translation. Investing in a basic machine translation tool can save money and time while still providing quality translations.
Huge Language Sections
It's estimated that there are over 7,000 spoken languages in the world. With companies having thousands of employees from different backgrounds, a human translator is often needed to facilitate communication. Machine translation software can make things even easier.
For instance, companies like AirAsia use machine translation software to enable communication between more than 22,000 employees of 16 different nationalities. Many of these employees don't speak English, so machine translation tools have proven invaluable.
Machine translation software can easily handle large language sections, translating text between English and other languages without any issues.
While some industries require short, relatively simple translations, some require complex and highly customized translations. Law firms often need waw translations for court proceedings. On the other hand, medical organizations require precise, human-quality translations that consider specialty terminology.
Fortunately, machine translation tools can be customized to fit your organization's needs. As one of the premier experts on machine translation technology, Bureau Works provides custom automated translation solutions for a wide range of customers.
No matter how far a given technology progresses, at the end of the day, it’s still a machine; it can make mistakes and won't be able to translate every single sentence perfectly. That's why 50% of all translations now combine human and machine translation technology.
Machine translation tools allow you to quickly translate text, leaving post-editing for humans with a better understanding of the language and context. That way, companies can ensure that they don't miss any important details and protect their companies.
Best Machine Translation Tools
As you might've assumed, there are many different machine translation tools. But prominent players in the tech industry, unsurprisingly, are at the top of the game. These companies use neural machine translation (NMT) technologies to power their engines.
That means that are constantly learning new languages and improving accuracy. Examples of the best machine translation tools we have, include:
The most widely-used machine translation software in the world. Google Translate can provide translations in over 100 languages, making it a great resource for companies and individuals alike.
Now, Microsoft Translator is more than just a machine translation engine. Microsoft's machine translation software offers interactive conversation translator, voice-to-text, and text-to-speech features that make it useful for a variety of different applications.
Closely associated with Amazon Web Services, the machine translation engine is known for providing hyper-accurate translations of certain languages. Chinese, Japanese, German and French are some of the languages Amazon Translate understands the best.
Watson Language Translator
IBM's language translation engine is considered one of the most advanced in terms of accuracy and speed. Watson's machine translation software integrates with Watson Studio and Due and often provides far more accurate translations than other engines on the list.
An independent machine translation software solution, DeepL Translator is known for providing translations that are often indistinguishable from existing human translations. It's the fastest-growing translation engine in the world, with thousands upon thousands of new users monthly.
Considerations for Machine Translation
The world is becoming more and more connected. Language consideration and cultural implications are integral to communication in a global economy. Companies need modern machine translation tools to export products successfully, manage a remote workforce, and conduct business overseas.
But how can you pick the right tool for you? Here are five things you need to consider when selecting a language translation technology tool:
Budget You're Working With
Translation services, on a large scale, aren't always cheap. The market as a whole is worth $6.6 billion in the United States alone, and if you want a quality service, you need to be prepared to pay for it.
So the first thing you need to consider when selecting a machine language translation tool is the budget you're working with. There are free tools out there, certainly. However, they come with limitations like restricted language support or medium-to-low accuracy.
You need to scale your budget to the number of languages you plan to translate and their complexity.
Every industry has its own words, phrases, and abbreviations that are specific to it. It's essential for any MT tool you choose to use these terms and provides accurate translations for them.
Finance, legal, manufacturing, e-commerce, medical, and many other industries have their own distinct language. If your industry doesn't involve complex,, you might not need to worry too much about accuracy.
But for most, looking at the capability of an MT service in your industry is essential. Bureau Works, for example, is proficient in financial, legal, and medical translations, among others.
Are you looking to translate your content into a language that has multiple dialects? Or from one language to another? Pay attention to the language pair you need. What are language pairs?
A language pair is an identifier used to describe a combination of two languages in the text translation process. Now, certain language pairs work better than others.
A Latin-based language, for instance, might not be translated into a Slavic language 100% correctly and vice-versa. Conversely, some language pairs like English and French are closely related, so accuracy won't be an issue.
Amount of Translation Needed
The next consideration is quite simple. Do you need large quantities of content processed and translated or just a few sentences?
The amount of translation you need dictates the engine you choose. For example, if you're looking for large volumes over a period of time, you might go with a paid cloud-based service. But if you need to translate a few pages, then you can use a free engine like Google Translate.
Customer vs. Employee Content
We've discussed this earlier - machine translation tools are great for both customer-orientated content and internal documents. The two require different levels of volume and accuracy, so it's important to choose a tool that can handle both.
Customer-orientated content like sales copies needs to reflect brand identity, connect with consumers, and have a high accuracy rate. That's why it requires a sophisticated combination of machine translation and-editing services.
Internal documents like reports and emails don't need to be fully accurate. These can be translated quickly with a free tool.
Is ChatGPT a Translation Tool?
In 2022, the world became mesmerized by DALL-E 2's ability to create realistic art based on short text descriptions. A few months after DALL-E, we started seeing the first pieces of content created by ChatGPT. The AI-based system could generate complex stories based on a few query words and phrases.
Not only could ChatGPT generate stories from scratch and translate existing text into other languages. But unlike common Machine Learning tools, ChatGPT uses a Large Language Model (LLM), which responds to user prompts by processing massive amounts. The input becomes ChatGPT's basis for predicting an outcome based on the user's instructions.
People have already tested ChatGPT as a translation tool, and the results were surprisingly good. For instance, multiple Reddit users used it to translate jokes, tweets, and Telegram posts. The translations, turns out, were on the same level as those of Google Translate and DeepL.
All in all, ChatGPT is a free tool that can actually help you with a number of tasks. In fact, the purpose of the tool is the take over the more monotonous aspects of emails and paperwork, so you can focus on customer-oriented and creative tasks.
So if you're looking to translate a short text quickly and mostly accurately, don't be afraid to use ChatGPT. However, if you're looking for a more precise and brand-focused translation, you should always go for a professional, human translation service.
The reality is that automated translation works best as an aid in the translation process and should not replace human translation.
The economy of the 21st century is, and will remain, global. Companies must explore new strategies and technologies to adapt to the changing business landscape. Machine translation is a great tool for improving workflow and increasing efficiency. It can help you create more content for a wider audience, and it's cost-effective as well.
Of course, it's important to weigh your options with care. It all depends on the content you create and want to translate. Do your homework. Make sure to find out what type of machine translation engine is best for you and the amount of content you need to be translated.
Here at Bureau Works, we've got you covered. Our team of experts can help you with machine translation, no matter the industry. If you need complex translations, our post-editing services can help you get the desired accuracy and brand identity.
Don't wait anymore. Contact us today, and let us help you grow your business on a global scale.