Neural machine translation is a particularly interesting niche field of artificial intelligence. This is because – traditionally – accurately translating one language into another can be difficult for a machine to achieve. Here, in this article, we are going to take a look at the technology that has and is adapting to do this job: neural machine translation.

 

Challenges of Machine Translation

All current languages have grammar rules and their own phrasing intricacies. When speaking, though, these aren’t always adhered to. Most people talk in shorthand or use some form of slang. In addition, there are words and phrases in some languages that may not have a direct translation into another.

The challenge has traditionally been that machines couldn’t keep up with this fluidity and ambiguity. This is because the old standard, statistical machine translation (SMT), worked on rule-based factors to create a direct translation. In other words, this software was run by the semantic, lexical, and syntactic rules that linguists laid out. This rule-based machine translation (RBMT) didn’t leave much room for growth and it limited what the programs could do.

How Is Neural Machine Translation Different?

Neural machine translation (NMT) differs from SMT because it uses an artificial neural network (ANN) rather than strict rules. ANNs are modeled after biological neural networks such as the human brain. The goal behind this is to create an AI system that can “think” rather than simply complete an assigned task. This allows the AI to process factors in translation such speech patterns and phrasing.

Another benefit of ANNs is that alongside thinking, they are also learning. This means that the more this AI translates languages, the better it will become at performing this job.

The Future of Neural Machine Translation

As of right now, NMT isn’t as widely implemented as SMT. A part of this is that it isn’t as developed as SMT. While more effective, NMT is still being further developed and learning new tricks. This only makes sense – such a complex system as this takes time to fully flesh out. However, as the technology has made it’s advancements, it will most like going to see wider use and distribution.

As for the fear of automation and replacement of the job of human translators, this is a far off of a worry. Experts in the field predict that it will be a while before these learning AI systems will be able to think on the same level as human rather than simply compute information in a robotic manner.

You can read more about Neural Machine Translation on the following sites:

3 Reasons Why Neural Machine Translation is a Breakthrough

https://slator.com/technology/3-reasons-why-neural-machine-translation-is-a-breakthrough/

Microsoft: What is a neural machine translation (NMT)?https://translator.microsoft.com/help/articles/neural/