* Provision the Language service resource in Azure.
* Deploy a Docker container to an on-premises server.
* Run the container and query the prediction endpoint.
* According to the Microsoft documentation, the Language service is a cloud-based service that provides various natural language processing features, such as sentiment analysis, key phrase extraction, named entity recognition, etc. You can provision the Language service resource in Azure by following the steps in Create a Language resource. You will need to provide a name, a subscription, a resource group, a region, and a pricing tier for your resource. You will also get a key and an endpoint for your resource, which you will use to authenticate your requests to the Language service API.
* According to the Microsoft documentation, you can also use the Language service as a container on your own premises or in another cloud. This option gives you more control over your data and network, and allows you to use the Language service without an internet connection. You can deploy a Docker container to an on-premises server by following the steps in Deploy Language containers. You will need to have Docker installed on your server, pull the container image from the Microsoft Container Registry, and run the container with the appropriate parameters. You will also need to activate your container with your key and endpoint from your Azure resource.
* According to the Microsoft documentation, once you have deployed and activated your container, you
* can run it and query the prediction endpoint to get sentiment analysis results. The prediction endpoint is a local URL that follows this format: http://<container IP address>:<port>/text/analytics/v3.1-preview.4/sentiment. You can send HTTP POST requests to this endpoint with your text input in JSON format, and receive JSON responses with sentiment labels and scores for each document and sentence in your input.

Explanation
Box 1: Cognitive Service User
Ensure that the members of a group named Management-Accountants can approve the FAQs.
Approve=publish.
Cognitive Service User (read/write/publish): API permissions: All access to Cognitive Services resource except for ability to:
1. Add new members to roles.
2. Create new resources.
Box 2: Cognitive Services QnA Maker Editor
Ensure that the members of a group named Consultant-Accountants can create and amend the FAQs.
QnA Maker Editor: API permissions:
1. Create KB API
2. Update KB API
3. Replace KB API
4. Replace Alterations
5. "Train API" [in new service model v5]
Box 3: Cognitive Services QnA Maker Read
Ensure that the members of a group named the Agent-CustomerServices can browse the FAQs.
QnA Maker Read: API Permissions:
1. Download KB API
2. List KBs for user API
3. Get Knowledge base details
4. Download Alterations
Generate Answer
Reference:
https://docs.microsoft.com/en-us/azure/cognitive-services/qnamaker/concepts/role-based-access-control

To upload your data, navigate to the Speech Studio . From the portal, click Upload data to launch the wizard and create your first dataset. You'll be asked to select a speech data type for your dataset, before allowing you to upload your data.
The default audio streaming format is WAV
Use this table to ensure that your audio files are formatted correctly for use with Custom Speech:

Reference:
https://docs.microsoft.com/en-us/azure/cognitive-services/speech-service/how-to-custom-speech-test-and-train