+65 6681-6632
8 Jurong Town Hall Road, #25-02 The JTC Summit. Singapore 609434
en

Neural Machine Translation

Neural Machine Translation

What it is, why it is better, and what to watch out for

Neural machine translation (NMT) is a still-novel approach to automatic translation based on artificial neural networks, vast “webs” elements interconnected not unlike neurons in animal brains.

As of 2020, neural machine translation is almost universally accepted as the most accurate, fluent, and versatile approach to automatic translation.

 

Main benefits of adopting Neural Machine Translation


Real-time delivery

With machine translation, you don’t have to worry about your content getting stale while it’s being translated. This is especially crucial for fast-paced sectors such as mobile app development, where updates can happen several times a week.


Near-human voice

NMT finally clears machine translation of its notorious clumsiness and non-natural structures. Especially with low- to mid-complexity texts such as online reviews, the translation quality is almost indistinguishable from a human!


Automation

Through just a bit of engineering, you can make your app, website, or video game automatically “feed” its texts to an NMT engine hosted in the cloud — and have the translations pushed back right to your repo. That’s a huge work-saver!

What businesses will benefit most from Neural Machine Translation

  • App & video game developers
  • Website & blog owners
  • E-commerce providers & platforms
  • E-learning providers & platforms
  • Media companies

How not to choose the right neural machine translation engine

Here are some guidelines to make sure you make the most from your NMT experience:

  • Specialised over generic. If an engine translates “all to all” languages, there’s a high chance that the quality will go down. NMT engines specialising in a few languages, such as AISA MT, will catch the nuances of those languages much better.
  • Proprietary over public.Public MT engines such as ones from Google or Microsoft are trained on the very texts you feed them to translate. If these texts are sensitive, such as in a contract, they may get accidentally outed to other users of the same engine.
  • Consider post-editing. If your text is critical, it might make sense to order a post-editing[link to the post-editing service to rule out any mistakes. It may cost you more than just an MT package, but for some types of content the cost of a mistake can be much higher.

A bit of tech talk: Neural vs Statistical Machine Translation

Since its invention in the mid-2010s, NMT has become the most advanced machine translation technology. It surpasses the runner-up, statistical machine translation, in almost all respects, from fluency to generalization.

Both MT technologies share the same basic approach: Engines are created based on large bilingual “corpora” — sets of texts that are already available in both languages. The difference is as follows:

  • Statistical MT engines do a “brute-force” matching of words and phrases that it finds in both languages. This is effective for “simple” matchings such as “I love you” versus “我爱你”, but gets much worse in less obvious examples.
  • Neural MT engines, on the other hand, use state-of-the-art deep learning algorithms. This allows them to encode and decode meanings that go far beyond superficial word structures and be truly context-dependent.

Get In Touch

captcha