Google Helps Developers Build Applications that Understand Human Language
Building on a raft of machine learning-related announcements it made earlier in the year, Google has just launched two new machine learning APIs into beta.
The most exciting of the two looks to be the new Google Cloud Natural Language API, which is aimed at helping developers build applications that understand human language. The API works by letting users reveal the structure and meaning of a text, and is available in English, Spanish and Japanese for now, with the promise of support for additional languages to come.
In a second blog post focusing on the Cloud Natural Language API, Google demonstrates how it can be used to analyze a report in the New York Times. Per Google’s example, you can perform sentiment analysis on various blocks of text using the API, run the results in a BigQuery table, and then use Google Data Studio to visualize them:
In a second example, Google showed how digital marketers can use the sentiment analysis capabilities in the Cloud Natural Language API to monitor customer calls to service centers and online reviews. Besides this, the API can also be used for entity recognition, for example to label entities as a person, location, or organization. Lastly, the API can also be used for syntax analysis, Google said.
Also entering beta today is Google’s Cloud Speech API, which uses the same voice recognition technology that powers Google Search. Using the API, developers can take advantage of speech-to-text conversion in over 80 languages for various apps and Internet of Things devices. According to Google, over 5,000 companies signed up to use the Alpha release of the Cloud Speech API.
Google Sentiment Analysis
In a busy day for Google Cloud Platform, the cloud giant also announced the opening of a new west coast region in Oregon. To begin with the new region will offer Google Compute Engine, Google Cloud Storage and Google Container Engine services, with more planned for later. Google says that by opening the new region, it should help to reduce application latency from between 30 percent and 80 percent in cities such as Los Angeles, Portland, San Francisco, Seattle and Vancouver.
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