Neural networks in Machine Translation – Beginner’s Guide

If you are a social media user, you may have seen the translate option on Social Media. The Translate now link shows up if anyone writes in a language that is different from your usual settings. When you click on it, the foreign language comment, tweet or post is automatically translated into English.

This translation has been done by software. But how can a computer program understand and translate languages as a human does? The technology behind automatic translation services is called machine translation. This article is a complete guide on how machine translation works, its benefits and challenges, and how can use this technology to grow your business. But first, let’s start with some basics!

What is machine translation?

Machine translation is a technology that uses Artificial Intelligence (AI) to translate from the source language to the target language without human assistance. The translation goes beyond simple word-to-word changes. Machine translation technology analyzes all text elements in the source language to comprehend the sentences. It understands context, references, and the way words influence each other. It then communicates the full meaning of the source language in the target language.

For example, the English sentence “We saw the play” translates as “Nous avons vu la pièce” in French. But the sentence “We play” translates as “Nous jouons” The word “play” changes in meaning due to the changing context. Such subtle language nuances are captured by machine translation technology.

How does machine translation work?

Computer scientists have been trying to teach computers to learn a language since the 1950s! Most early attempts failed due to limitations in hardware and processing power. Eventually, developers began using language databases and statistical rules to translate text. They created software “dictionaries” that contained syntax rules for computers to understand. However, this process took up a lot of time and manual effort. Every new language required engineers to begin the process again from scratch. Each added language required them to start over with the development process. The translations were also inaccurate and required human correction.

However, much has changed in the last 70 years! The advent of AI brought a new era in machine translation. We now use neural networks to process and translate languages. Neural networks are accurate, can translate into multiple target languages simultaneously, and are lightning-fast!

Neural networks—the technology behind AI

A neural network is made of interconnected computing nodes that work together to solve complex challenges. For translation, the source language is input into the network as data. Every node in the network makes small changes to the data until the final output is the translated text. For example, one node identifies the nouns, verbs, and other grammatical components. Another node translates the nouns and so on. But every node always considers the whole input sentence when translating.

Training the neural network

Neural network design is based on the human brain. Just like humans learn a new language, developers and Computational Linguist train the neural network to understand language nuances in different domains. Language experts and computer engineers work together so the neural network can translate legal, financial, and medical jargon accurately.

For example, the English term banknote should translate into the formal term for money in a foreign language. Without proper training, it may get translated into generic terms like “ticket.”

Self-correction and self-learning

You can use layers of interconnecting nodes to create a complex, deep-learning neural network. Such networks self-correct. They are given an initial data set of correct translations. When they translate an unknown sentence, they verify it with the known data set. Any mistakes are corrected and the knowledge of the error is passed back to all the nodes. The system thus “learns” from the error and keeps getting more accurate with every translation!

How do businesses use neural machine translation?

Businesses use neural machine translation for all types of use cases. For example, the short-term holiday rental company, Airbnb, uses the technology to automatically translate accommodation descriptions for its users. If a Japanese guest wants to book a room in the US, he can read all the English listing descriptions in Japanese!

Some other use cases include:

Translation of internal company documentation for employees in different locations or from different cultures.
Translation of product documents for global partners and international customers.
Translation of user-generated content like social media content, comments, and reviews for analytics.
Translation of customer requests to increase the scale and scope of online chat-based customer service.
Translation of legal documents on a large scale for legal research or contracting.

What are the benefits of neural machine translation?

Neural machine translation systems are universally accepted as the most fluent, versatile, and accurate translation systems! They bring four main benefits to your business

Speed without loss in accuracy

You get real-time translation that is nearly 100% accurate. For example, your customer types a query in their language of choice in your app chat box. Your service assistant sees the chat in the language they can work in! There are no delays waiting for a translator and your customer service remains accessible and fast.

High-volume translation in a short time

Neural machine translation can translate millions of words instantaneously. You can process large volumes of documents in a short span of time, increasing productivity and reducing time to market. For example, you can integrate your content management system with machine translation to automatically organize and tag content before translation.

Wide variety of language choices

Neural networks can support many languages simultaneously, so you get the same text auto-translated into multiple languages at once. For example, Systran Translate Pro supports 50+ languages and over 140 language combinations!

Cost-effective translation services

Neural machine translation can be incredibly cost-effective. You can use pre-trained systems to translate what you need. You only have to pay for what you use. For example, Systran Translation services start from as little as 5 euros per month per user.

Does neural machine translation require human verification?

There are some misconceptions that machine translation is inaccurate. Sometimes machine translation may miss finer nuances like humor or sarcasm. But it works perfectly well for most business use cases.

Machine translation does most of the hard work and reduces the load on the human translator. The translator works with the Machine Translation Software, helping him/her to handle huge volume of documents and allow him/her to improve productivity. The translator can post-edit the translations, and this “hybrid” solution is great for businesses.

Additionally, mature machine translation systems have received exceptional training. For example, at Systran, a global team of language experts trains and maintains our neural networks. They also perform additional training for specific business domains and use cases. Their neural networks translate hundreds of thousands of documents everyday. A well-trained and mature system is a great help for human tranlator!

Conclusion

Neural machine translation is a must-have for companies that work with a global network of customers and partners. Now that you know how neural networks work for translation, you can be more confident with using the system. However, it’s important to choose the right neural machine translation provider who has trained their neural networks as per your requirements!