The Microsoft Azure Lanugage Understanding Service is an Azure cloud service, which provides Lanugage understanding using sophisticated AI.
First of all, we need to create a Language Understanding resource in the Azure Portal:
Then, after creating the LUIS resource, we need to copy one of the Cognitive Service API access keys:
Then, navigate to the LUIS console, then create an authoring resource:
Next, we need to create a new Conversation app:
After creating the Conversation app, go to the Manage section and copy the APP ID:
Then to the versions screen:
Then, click on the Import as LU button and select the ROS_roam.lu file. Mark the imported version as activated.
Now, go back to the Build section to see the imported intents:
Now, go to the speech studio website and select Custom Keyword in the Voice assistant:
Then create a new project:
Then, create the first model dedicated for invoking the robot:
In the next step, select a prononciation and hit next to define the model type:
Then, we need to create an other model to stop the robot:
After creating the two models, we need to download the created models. To do that, click on the model and hit the download the model:
The downloaded Zip files contains .table files that you need to place them in a known location.
Once you have completed the model, you can train and publish to a production slot. This will require you to associate the model with a prediction resource on Azure. Once that has been completed, you can configure the ROS node.
IMPORTANT: a second model is needed to handle the STOP robot command. The Keyword created for the Stop Model will be used to immediately stop the robot.
The ROS node requires the following information from the LUIS console
NOTE: LUIS is available as a containerized deployment: Check instructions here.