What is Neural Machine Translation?

If you’ve ever wondered how Google Translate and other similar applications can provide such fast and accurate translations, you’re about to find out. The answer is Neural Machine Translation (NMT) – a groundbreaking technology that has revolutionised the field of translation. It’s a hot topic for anyone interested in translation and localisation and its impact on the industry is undeniable.

 

In this blog post, we’ll demystify the concept of Neural Machine Translation, exploring what it is, how it works, and what sets it apart from traditional machine translation. We’ll also delve into the practical applications of NMT in various industries and contemplate its future in a world where cross-cultural communication and understanding have never been more important.

 

What Is Neural Machine Translation?

Neural Machine Translation (NMT) is a form of machine translation that leverages artificial neural networks to convert text or speech from one language to another. Unlike traditional methods, NMT processes whole sentences simultaneously, allowing for more contextually accurate translations.

 

Deep learning, which is a subset of artificial intelligence, was the fundamental technology that enabled Neural Machine Translation. Deep learning allows computers to recognise patterns in large datasets. Modelled on the human brain, these systems are comprised of several layers of artificial neurons – small mathematical functions that process data in the form of electrical signals. These neural networks are able to recognise the patterns in language, which allows them to accurately and quickly translate whole sentences.

 

With enough training data, neural networks can learn to translate with impressive accuracy. This type of machine translation can even handle complex sentences, idiomatic expressions, and slang. NMT systems can also better understand the context of a sentence, allowing them to produce more natural-sounding translations.

 

Neural Machine Translation vs Machine Translation

Anyone who remembers the early days of Google Translate probably associates machine translation with literal translations that are often inaccurate and even comical. While traditional machine translation methods are still used in some contexts, they lack the accuracy necessary for professional translations and other sensitive applications. So, what is the difference between neural machine translation and machine translation?

 

Traditional machine translation is rule-based, meaning it relies on pre-programmed rules to process the text and determine how it should be translated. This type of translation is often limited in its ability to adapt to context, making it difficult to handle colloquialisms, idioms, and other nuanced language features. There’s another problem too – it’s difficult to create enough rules to cover every situation. Language is incredibly nuanced and varied, making it almost impossible to create pre-defined rules that cover every possible context and language variation. It’s also incredibly labour-intensive and time-consuming to create and maintain these rule-based systems.

 

Machine translation has existed for several decades and it’s served its purpose in certain contexts. However, the advent of neural machine translation was a major breakthrough in the field of translation. Unlike rule-based translators, Neural Machine Translation (NMT) is trained to recognise the patterns in language data and then generate translations based on those patterns. Effectively, NMT teaches itself how to translate through artificial intelligence and deep learning. It doesn’t require the same amount of programming or labour-intensive rule creation as traditional machine translation, and this means it’s far easier for more languages to be added and managed. As long as there is enough training data, NMT can learn the patterns in language and generate translations.

 

Real-World Applications of Neural Machine Translation

Neural Machine Translation (NMT) is used in a variety of real-world applications. It is particularly useful for quick and accurate translations of large volumes of text, such as documents or websites. This makes NMT useful for many businesses that need to translate a range of content quickly and accurately. Here’s a look at some of the key applications:

 

Online Translation Tools

You’re probably familiar with this application. NMT is the technology behind popular online translation tools like Google Translate. By processing large chunks of text in one go, NMT can provide quick, accurate translations that take context into account, making these tools far more reliable and usable than their predecessors. Google Translate is freely available and is now used by over 500 million people on Android alone. It has an enormous library of languages for which it can provide translations (currently over 100), and this number is growing.

 

Customer Support

NMT has seen significant uptake in customer support contexts, especially in global companies that have to cater to customer queries in multiple languages. NMT allows these businesses to provide fast and accurate responses, giving customers a better experience and improving customer satisfaction.

 

E-commerce

In our increasingly connected world, businesses are selling to customers in many different countries, which means dealing with multiple languages. NMT allows businesses to translate product descriptions, reviews, and customer queries quickly and accurately, allowing them to easily scale their localisation efforts.

 

Social Media Monitoring

Companies frequently monitor social media for mentions of their brand, customer complaints, and market trends. However, this becomes challenging when the posts are in multiple languages. NMT assists in accurately translating these posts, allowing companies to gain a much clearer understanding of what people are saying about their brand.

 

Localisation of Content

Whether it’s translating a website, a software application, or a video game, NMT plays a key role in localisation – the process of adapting content to a specific region or language. NMT provides more accurate translations and can save significant time and money for companies that want to expand into new markets.

 

Language Learning Apps

NMT has also found a home in language learning apps, providing accurate translations to help users learn new languages. It’s also used in these apps to power features such as real-time translation and speech recognition.

 

Can Neural Machine Translation Replace Human Translation?

One of the most hotly debated questions surrounding Neural Machine Translation (NMT) is whether it could one day replace human translators. After all, it’s faster, more scalable, and, with each advancement, is becoming more and more accurate.

 

However, while NMT has undeniably transformed the translation industry, it’s important to acknowledge its limitations. Despite the significant strides in accuracy, there remain scenarios where human translators have the upper hand.

 

Missing the Big Picture

While NMT has become proficient at understanding the context within a sentence or a paragraph, it can still struggle with understanding the broader context of a document. Human translators are able to comprehend the overall narrative or argument of a text and make translation decisions accordingly. This understanding of the wider context is crucial when translating complex or nuanced texts like literature, legal documents, or academic papers.

 

Difficulties with Nuance

Human translators are able to pick up on cultural nuances, connotations, and emotions in the text, which NMT systems can still sometimes miss. For instance, a phrase that’s seen as casual in one culture might be deemed disrespectful in another. Sometimes, striking the right tone is simply too subtle for NMT systems to accurately identify. Similarly, humour, irony, and idioms can be challenging for NMT to translate accurately.

 

Lack of Training Data 

The quality of NMT’s translation depends heavily on the quantity and quality of the training data. Languages that are less represented on the internet or in digitised text might not have sufficient high-quality data available for NMT to learn from. In such cases, human translators, especially those who are native speakers, can provide far superior translations.

 

To sum up, while Neural Machine Translation is an incredibly powerful tool that has revolutionised the translation industry, it’s not yet ready to replace human translators entirely. For large-scale translations, NMT may be able to handle the bulk of the translation work, but it’s still necessary for human translators to oversee the quality of the translation and step in for tasks that require a higher level of cultural understanding, creativity, or subject-matter expertise.

 

The Future of Neural Machine Translation

As we look to the future, there’s a lot of anticipation and excitement surrounding Neural Machine Translation (NMT). It’s clear that the technology has enormous potential, and we’ve only begun to scratch the surface of its capabilities. Here’s a glimpse at what we can expect looking forward.

 

Improved Accuracy and Quality

In terms of improvements, we can expect the accuracy of translations provided by NMT systems to continue to improve. This is thanks to two factors: the increasing sophistication of neural networks and the ever-growing amount of linguistic data available for training. As the internet continues to grow, and as more diverse languages and dialects are represented online, the training data available for NMT will become more comprehensive, leading to more accurate translations.

 

Faster Translations

We may also see more advancements in the speed and efficiency of NMT systems. This could be achieved through improvements in hardware, software, and the neural networks themselves. Faster and more efficient NMT systems will allow for better real-time translation applications, such as instantaneous speech translation, making communication across different languages even easier.

 

Personalised Translations

Another exciting prospect for NMT is increased personalisation. As machine learning technologies advance, NMT systems can potentially adapt to individual users’ language patterns, including their unique phrases, slang, or tone. This could lead to translations that not only translate the words of a text but also capture the individual personality and style of the author.

 

Ethical Considerations

As with any AI technology, ethical considerations will also shape the future of NMT. Concerns about privacy, data security, and the representation of different languages and cultures will need to be addressed as the technology advances. What is certain is that NMT will continue to revolutionise the way we communicate across languages and make localisation and translation more affordable and accessible to everyone.

 

Partner with a Translation Agency to Harness the Power of NMT

If your business or organisation needs to translate text in multiple languages, partnering with a translation agency is a great way to make use of the advanced technology offered by NMT. Here at LingvoHouse, we combine neural machine translation with talented human linguists to provide accurate and cost-effective translations. Our team of experts is also available to provide advice on the most suitable technology for your project and provide a bespoke package of services. Contact us today to find out more.