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Azure Cognitive Services – Language APIs

In today’s post focusing on Azure Cognitive Analytics, I’ll look at the Language Analytics APIs that are available. These language APIs allow your apps to process natural language with pre-built scripts, evaluate sentiment and learn how to recognize what users want. Often, you’ll work with Speech and Language APIs together, but I’ll cover Language today and Speech in my next post.

Here’s what is available in the Microsoft Language stack:

1. Language Understanding Intelligence Service (LUIS) – The most commonly used in this stack; with it you can teach your apps to understand commands from your users. UPS uses this to help customers track their packages. It’s also a great way to interact with Azure Bot Service where you can go in and ask questions in a bot and it will do the job of understanding what’s been asked by understanding the language being used.

2. Text Analytics API – This can easily evaluate sentiment and topics to understand what users want and use the language and context to decipher whether a person is happy or not, for instance. Let’s say you use this with a customer survey and it will do some analytics to identify words like wonderful or terrible. It provides sentiment analysis for the organization. You can move to another interaction level and respond, whether it’s ‘thanks for the great review’ or ‘sorry you had a bad experience, how can we help?’

3. Bing Spell Checker API – You can attach the Bing Spell Checker API to your application and it will detect and correct spelling mistakes.

Check out Azure Data Week coming in October 2018

4. Translator Text API – This API will translate the text that typed in between languages, so you can work with third parties in other countries or provide customer service in a chat scenario when you’re interacting with a person in another language. There are a lot of languages supported.

5. Web Language Model API – Helps us handle natural language queries by using the power of predictive language models trained on web-scale data and understanding the next common word or providing word completion.

6. Linguistic API – Currently in preview but brings in some very sophisticated linguistics technologies to simplify complex language concepts and parse text.

DataOnWheels

Steve Hughes is a Principal Consultant at Magenic. His area of expertise is in data and business intelligence architecture on the Microsoft SQL Server platform. He was also the data architect for a SaaS company which delivered a transportation management solution for fleets across the United States. Steve has co-authored two books and delivered more than 30 presentations on SQL Server and data architecture over the past six years. He also provides insights from the field on his blog at http://dataonwheels.wordpress.com.

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