Conversational Language Understanding (CLU) in Azure Language Service

Introduction

Conversational Language Understanding, offered by Azure AI Language, is a cloud-based service that machine learning to help you create a natural language understanding component for your conversational applications.

This means it enables your applications to understand and respond to human language in a more natural and context way, making your chatbots or virtual assistants smarter and more effective in conversations with users.

Azure AI Language provides the tools and capabilities to enhance the language understanding aspect of your conversational applications, making them engaging for users.

Steps to create the CLU project

1. Login to the language studio https://language.cognitive.azure.com/
2. In the “Choose a language resource” window, select or create a new language resource.
3. Choose the language you want to work with from the “Create new” option.
4. Click on “conversational language understanding”.

5. After creating the project, proceed to schema definition by clicking on the project.

ADDING INTENTS

1. Add Intents that are goals or purposes behind a user’s input or message and add them to the intents list.
2. Click on the intent to load the Data labeling interface.

ADDING UTTERANCES

1. Select the “intent” and Write the utterances for that intent.
2. Click “Enter” to add the utterances to the list and save your changes.

TRAIN A MODEL

1. Go to the “Train model” section, usually found in the left-side menu.
2. From the top menu, Select “Start a training job”.
3. If you want to create a new model, select “Train a new model” and provide a name for the new model.

4. Alternatively, if you wish to replace an existing model with one trained on new data, select “Overwrite an existing model” and then choose the existing model you want to replace. Keep in mind that overwriting a model is irreversible.

5.Click “Train” to start the training process.

DEPLOY A MODEL

1. After training, review the model’s evaluation details.
2. Go to “Deploying a model” in the left side menu.
3. Select “Add deployment” and create a deployment name.
4. From the dropdown menu, pick the trained model for this deployment or choose to overwrite an existing deployment with a new model.

7.Click “Deploy” to proceed with the deployment.

TEST A MODEL

1. In the “Testing deployments” section, select the deployment associated with the model you want to test.
2. In the provided text box, enter the specific utterance you want to test. For example, if you’re testing an application for email-related queries, you enter “Delete this email.”.
3. At the top of the page, click “Run the test” to initiate the testing process.

These steps guide you through the process of creating a CLU project ,adding an intent , deploying and testing the model.

Conversational Language Understanding is the key to more natural and effective interactions in the world of AI. Better language understanding leads to better conversations. Stay tuned for exciting developments in this field.