Build a Conversational Language Understanding Model

By Ashwin Venugopal -

 





Introduction

You may develop a model that apps can use to extract meaning from natural language using the Azure AI Language Conversational Language Understanding service (CLU).

Software must be able to handle text or speech in the natural language format that a human user would write or speak. This is known as Natural Language Processing, or NLP. Natural Language Understanding (NLU), a subset of Natural Language Processing (NLP), addresses the challenge of deriving semantic meaning from natural language, typically through the use of a trained language model.

Azure AI Language enables developers to build apps based on language models that can be trained with a relatively small number of samples to discern a user's intended meaning.

Understand Prebuilt Capabilities of the Azure AI Language Service

The Azure AI Language service offers a number of tools for comprehending human language. You can use each feature to better communicate with users, better understand incoming communication, or use them together to provide more insight into what the user is saying, intending, and asking about.

Azure AI Language service features fall into two categories- Pre-configured features, and Learned features.

To utilize these functionalities in your application, you need to direct your query to the corresponding endpoint. The endpoint for querying a particular feature differs, but they all start with the Azure AI Language resource you established in your Azure account, whether you are crafting your REST request or setting up your client with an SDK.

Conclusion

We have successfully learnt the basics of Azure AI Language service.

 

 

 

 










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