Feeds

Google's robot army learns Spanish

La rebelión de las máquinas

Intelligent flash storage arrays

If you want to learn another language, you need to spend time in the country, talk to people, get drunk and attempt to order complex drinks, and eventually read that country's great works of literature – unless you're Google, that is.

In a recent paper, three Googlers outlined a new approach to machine-based translation that uses the Chocolate Factory's weapons of choice: masses and masses of data, and neural networks.

The paper, "Exploiting Similarities among Languages for Machine Translation", shows how Google is able to use a small dictionary of pairs of words in two languages to train a network that can infer missing dictionary entries.

"Our method can translate missing word and phrase entries by learning language structures based on large monolingual data and mapping between languages from small bilingual data," they write. "This method makes little assumption about the languages, so it can be used to extend and refine dictionaries and translation tables for any language pairs."

The system works by visualizing the vectors of individual words, then projecting the vector from the source language to the target language and swapping in the word with that vector representation in that dictionary.

Google_machine_translation

Feeling nervous yet, human?

It is able to work because, the researchers explain, "all common languages share concepts that are grounded in the real world (such as that cat is an animal smaller than a dog), there is often a strong similarity between the vector spaces."

Google's technology relies on the Skip-gram or Continuous Bag-of-Words (CBOW) models proposed by Googlers in another, earlier paper, which found that word vectors could be used to infer other words. "For example, vector operations 'king' - 'man' + 'woman' results in a vector that is close to 'queen'."

These models let Google create neural network models that learn high-quality word vectors from vast datasets, and do so in a less compute-intensive way than ever before. This lets the company scale up the model far beyond previous limits.

"Using the DistBelief distributed framework, it should be possible to train the CBOW and Skip-gram models even on corpora with one trillion words, for basically unlimited size of the vocabulary," they wrote at the time. "That is several orders of magnitude larger than the best previously published results for similar models."

Now, the team has been able to put these models to use to train them to figure out the relationship between different words, and infer the vector representations of a word's counter in another language.

"Thus, if we know the translation of one and four from English to Spanish, we can learn the transformation matrix that can help us to translate even the other numbers to Spanish," they write.

The technique works for languages far more alien from each other such as English and Czech, and English and Vietnamese with high degrees of accuracy.

"In particular, our work can be used to enrich and improve existing dictionaries and phrase tables, which would in turn lead to improvement of the current state-of-the-art machine translation systems," they write. "Clearly, there is still much to be explored."

In other words, get tweaking the CV, translators, because Google's algo-army is coming for you. Comprender? ®

Security for virtualized datacentres

More from The Register

next story
Boffins who stare at goats: I do believe they’re SHRINKING
Alpine chamois being squashed by global warming
What's that STINK? Rosetta probe shoves nose under comet's tail
Rotten eggs, horse dung and almonds – yuck
Comet Siding Spring revealed as flying molehill
Hiding from this space pimple isn't going to do humanity's reputation any good
Experts brand LOHAN's squeaky-clean box
Phytosanitary treatment renders Vulture 2 crate fit for export
LONG ARM of the SAUR: Brachially gifted dino bone conundrum solved
Deinocheirus mirificus was a bit of a knuckle dragger
MARS NEEDS WOMEN, claims NASA pseudo 'naut: They eat less
'Some might find this idea offensive' boffin admits
prev story

Whitepapers

Choosing cloud Backup services
Demystify how you can address your data protection needs in your small- to medium-sized business and select the best online backup service to meet your needs.
Forging a new future with identity relationship management
Learn about ForgeRock's next generation IRM platform and how it is designed to empower CEOS's and enterprises to engage with consumers.
Security for virtualized datacentres
Legacy security solutions are inefficient due to the architectural differences between physical and virtual environments.
Reg Reader Research: SaaS based Email and Office Productivity Tools
Read this Reg reader report which provides advice and guidance for SMBs towards the use of SaaS based email and Office productivity tools.
Storage capacity and performance optimization at Mizuno USA
Mizuno USA turn to Tegile storage technology to solve both their SAN and backup issues.