Google Cloud Diary: GCP Speech API Gets New Languages, Longer File Support & Time Stamps

Sam Pudwell joined Silicon UK as a reporter in December 2016. As well as being the resident Cloud aficionado, he covers areas such as cyber security, government IT and sports technology, with the aim of going to as many events as possible.

GCP NEWS: Google Cloud Speech API improves speech recognition and adds more languages, plus all the latest Google Cloud Platform news

Google Cloud Platform (GCP) boasts thousands of high-profile customers around the world – from Spotify to Snapchat and Coca Cola – providing a huge range of services. These include tools related to big data analytics, the Internet of Things (IoT), machine learning, app development, security and many more.

Google is constantly working to keep pace with its main rivals Amazon Web Services (AWS) and Microsoft Azure in what is now a hugely competitive market, so here’s the latest news and updates on the public cloud provider.

Google Cloud Next 2017

August 2017: Google Cloud Speech API adds 30 new languages

Google Cloud Speech API can now handle longform audio more effectively and supports 30 new languages, covering one billion additional speakers.

The speech recognition technology can now support files of up top 3 hours in duration, up from 80 minutes, and there is the possibility of an extension on a case-by-case basis.

Google says it has also added time stamps for each word in a conversation – one of the most requested features from GCP customers.

Among the new languages are Bengali, Latvian and Swahili, bringing the total number to 119. Google says this allows for an almost global reach, helping customers to expand.

July 2017: Google opens London data centre region

Google has expanded the footprint of the GCP with the opening of a new data centre region in London, strengthening the company’s commitment to the UK in the face of Brexit.

The London base is only the Alphabet-owned company’s second European data centre region after Belgium, although it does also have plans to spread its wings further into Germany, Finland and the Netherlands later this year.

At the launch event, Google’s managing director of UK and Ireland Ronan Harris described the UK as “the home of digital and the home of digital innovation”, reiterating that the UK has plenty to offer the technology market even after it breaks away from the European Union.

April 2017: Elastic brings search and analytics to GCP


Google has partnered with California-based data firm Elastic to bring managed support of its open source search and analytics platform onto GCP.

The complete Elastic stack is now available in Google’s cloud, providing customers with multiple new features including increased security and privacy, data analytics and machine learning services and the tools needed to build applications.

Elastic co-founder and CTO Shay Banon said the partnership represents “a significant step forward for our users”, describing GCP as “one of the most innovative and open source friendly cloud platforms”.

March 2017: Google releases Cloud Container Builder on GCP

Google has strengthened its container offering on GCP as competition in the market continues to gather momentum.

Cloud Container Builder is now generally available on Google’s cloud service and boasts features such as a command-line interface, automated build triggers and build steps for executing build commands.

Google describes the service as “a stand-alone tool for building container images regardless of deployment environment”, which can be used by both large enterprises and startups.

The real sweetener for potential customers is that it comes with 120 free build-minutes per day, enabling most users to move their builds to the cloud at no cost and with none of the overheads of managing their own servers. Any additional build-minutes are priced at $0.0034/minute.

February 2017: GCP packs Nvidia GPUs for deep learning algorithms

neural networks

Google has made access to Nvidia graphics cards available on its Compute Engine and Cloud Machine Learning platforms, giving GCP customers access to additional computational power for training smart software and artificial intelligence (AI).

Offering such a service means companies working on software and systems that use machine and deep learning algorithms won’t have to have GPU clusters in their own data centres, thereby cutting hardware costs.

Deep learning and AI networks both require huge amounts of data analysis, something which traditional central processing units (CPUs) fall short on when compared to products such as Nvidia’s Tesla K80 graphics processing units (GPUs).

Google is of course not the only company providing cloud-powered deep learning systems, but this partnership will help to strengthen its offering in this area.

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