Simply put, neural machine translation (NMT) involves software used for translating words and sentences from one language to another. Classic examples of publicly accessible NMT software are Google Translate and Baidu Translate (Google’s Chinese equivalent). Many multinational corporations are utilizing NMT to help them overcome translation challenges related to their global expansion efforts.
- Google Translate is the most widely used machine translation tool around the globe. Its neural network significantly increases translation accuracy and fluency. The tech giant uses enormous data sets to train its translation algorithms and has an end-to-end design to boost learning over time.
How Does Neural Machine Translation Work?
Neural machine translation makes use of an extensive artificial neural network to predict the likelihood of a sequence of words. It typically models entire sentences in a single integrated model. Here are two ways to describe a neural network:
- A computational system that strives to mimic the billions of neuron cells in the human brain that use observable data (i.e., examples) to learn and make decisions.
- A kind of machine learning (a form of artificial intelligence) that uses statistical techniques to provide computers with the ability to learn.
How Does NMT Differ from Rule-Based Machine Translation (RBMT)?
Neural machine translation translates entire sentences at a time, rather than just piece by piece, which is what RBMT does. NMT is able to use the context of a sentence to come up with the most relevant translation. It then makes adjustments and rearrangements until the translation reads more like human speech with the correct grammar.
- Think about how humans translate. When we want to translate ‘The girl rides the bike,’ our brain first makes a mental representation of what that looks like. Once we have that, we can proceed to translate. NMT works in the same way.
The Architecture of Neural Machine Translation
NMT makes use of an encoder-decoder architecture. An encoding neural network is capable of reading and encoding a source sentence into a ‘meaning vector’ or ‘thought vector.’ This vector is a number sequence that represents the meaning of the sentence. A decoder then produces a translation from the encoded vector.
The encoder-decoder system is trained with large amounts of data to maximize the probability of producing a correct translation from a sourced sentence. This enables it to capture long-range dependencies in languages, such as syntax structures and gender agreement, resulting in much more fluent translations.
How Does Neural Machine Translation Benefit Users?
Neural machine translation is a single, well-trained system that can accurately translate source to target text. It does away with the need to use specialized systems that are typical of statistical machine learning. Its biggest strength is its ability to perform end-to-end direct learning.
NMT is applicable to pretty much any language, including ones that are comprehended by relatively few people. Users can fine-tune translations to suit specific types and styles of languages, e.g., UK-English, US-English, and medical, financial, and scientific language. Several industries requiring custom-developed and high-accuracy machine translation incorporate a blend of statistical and neural translation methods.
Neural Machine Translation and Localization
Localization teams work to meet the demand for localized content in global markets. NMT will increasingly help such teams to produce more accurate translations. However, until AI translations alone can 100% imitate the human brain, input from human translators will still be needed.
Why Use Localize?
Localize is a translation management and solutions provider that is always keeping an eye on future technical developments that can improve the quality of translations. Localize provides a number of machine translation options including Google translate, Amazon translate, and Microsoft translate. Contact us and become one of the 500-plus companies that we are assisting with their international marketing efforts.