Google Translate gets its biggest update with support for neural networks

Using neural networks, it will be working at improving speech recognition and computer vision.


Google translations, though helpful, are known to put users in an awkward situation several times. Google now tries to rectify it by bringing one of the biggest update to Translate with natural language translation. Using neural networks, it will be working at improving speech recognition and computer vision.

With the new update, Google Translate will utilise Google's neural machine translation system for translating phrases and will roll out to eight language pairs. English and Chinese were the first, followed by French, German, Japanese, Korean, Portuguese, Spanish and Turkish. It is believed that these language pairs will cover 35 percent of Google Translates. However, Google is said to eventually roll it out to all 103 languages.

In September, Google had deployed the Google Neural Machine Translation (GNMT) system in Google Translate for Chinese to English translation. The system handles 18 million requests every day. Chinese to English is a particularly hard language pair for machines to handle, and the system is expected to be rolled out to more language pairs.

The previous system used Phrase-Based Machine Translation (PBMT) that broke down the sentences to be translated into phrases and words for translation. On the other hand, Neural Machine Translation (NMT) considers the entire sentence as an input. When it was first tested, NMT results were as good as PBMT results. Then, Google engineers improved the accuracy of the NMT system by making it identify and treat rare and obscure words separately. These included bilingual humans to continuously rate the results of the NMT.

The Tensor Processing Unit

The Tensor Processing Unit

Eventually, Google engineers zeroed on a solution that was good enough to be deployed on Google Translate, to quickly and accurately handle the large volume of requests. The production deployment was possible because of the TensorFlow, an open source frame work for machine learning.

Besides, the company had lately announced a new Cloud Machine Learning API to help people find careers. Google Jobs API provides businesses with Google-strength capabilities to find, match and recommend relevant jobs to candidates. Cloud Jobs API uses machine learning to understand how job titles and skills relate to one another and what job content, location, and seniority are the closest match to a jobseeker’s preferences.Know more here.

Google blogpost states about making Cloud Vision API affordable to all. By offering the API at a more cost effective price, more number of organisations can take advantage of it. Click here to find out more.

machine-learning-day_001

Starting next, Google Cloud will also offer more hardware choices for businesses looking to use Google Cloud Platform (GCP). "For Google Compute Engine and Google Cloud Machine Learning, businesses will be able to use GPUs (Graphics Processing Units) that are highly-specialized processors capable of handling the complexities of machine learning applications. Making GPUs available in Google Cloud means that you can focus on solving challenging computational problems while accessing GPU machines from anywhere and only paying for what you need," the blogpost said.


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