This call batch analytics component is using Ingestion Client that helps transcribe your audio files without any development effort. The Ingestion Client monitors your dedicated Azure Storage container so that new audio files are transcribed automatically as soon as they land.
This tool uses multiple Azure Cognitive Services to get insights from call recordings. It uses Azure Speech to transcribe calls and then Azure Text Analytics for various analytics tasks (including sentiment analysis, PII detection/redection etc). Insights extracted by these Azure AI services are then stored to Azure SQL database for further analysis and visualization (using Power BI or other tools).
Think of this tool as an automated & scalable transcription solution for all audio files in your Azure Storage. This tool is a quick and effortless way to transcribe your audio files or just explore transcription.
Using an ARM template deployment, all the resources necessary to seamlessly process your audio files are configured and turned on.
The Ingestion Client is optimized to use the capabilities of the Azure Speech infrastructure. It uses Azure resources to orchestrate transcription requests to the Azure Speech service using audio files as they appear in your dedicated storage containers.
The following diagram shows the structure of this tool as defined by the ARM template.
When a file lands in a storage container, the Grid event indicates the completed upload of a file. The file is filtered and pushed to a Service bus topic. Code in Azure Functions triggered by a Service bus message picks up the event and creates a transmission request using the Azure Speech services batch pipeline. When the transmission request is complete, an event is placed in another queue in the same service bus resource. A different Azure Function triggered by the completion event starts monitoring transcription completion status. When transcription completes, the Azure Function copies the transcript into the same container where the audio file was obtained.
Follow these steps to set up and run the tool using ARM templates.
An Azure Account, a Azure Speech services key and a Azure Text Analytics service key is needed to run prior to deploying this tool using ARM template.
NOTE: You need to create a Speech Resource with a paid (S0) key. The free key account will not work.
Audio files can be processed either by the Speech to Text API v3.0 for batch processing, or our Speech SDK for real-time processing. We will be using the Batch Mode and make use of Diarization feature offered in the Batch Mode.
Follow the instructions below to deploy the resources from ARM template.
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In the Azure portal, click Create a Resource. In the search box, type template deployment, and select the Template deployment resource.
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On the screen that appears, click theCreate button.
- You will be creating Azure resources from the ARM template we provide. Click on click the Build your own template in the editor link.
- Load the template by clicking Load file. Use the
call-batch-analytics\batch-analytics-arm-template-servicebus.jsonfile in this step. Alternatively, you could copy/paste the template in the editor.
- Once the template text is loaded you will be able to read and edit the transcript. Do NOT attempt any edits at this stage. You need to save the template you loaded, so click the Save button.
Saving the template will result in the screen below. You will need to fill in the form provided.
Following settings are required to be completed in this step.
- Specify
Resource groupname. Recommended to create a new resource group. - Specify
Storage Accountname. Recommended to create a new storage accout. - Provide an existing
Azure Speech Services Key. - Select
Azure Speech Services Regionthat corresponds to your Azure Speech Services Key. - Provide an existing
Text Analytics Key. - Select
Azure Text Analytics Regionthat corresponds to your Text Analytics Key. - Provide
Sql Administrator LoginandSql Administrator Login Password. Make a note of this as we will need this in future steps.
Other setting are options. You can change them if you wish.
It is important that all the information is correct. Let us look at the form and go through each field.
NOTE: Use short descriptive names in the form for your resource group. Long resource group names can result in deployment error.
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Pick the Azure Subscription Id where you will create the resources.
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Either pick or create a resource group. (It would be better to have all the Ingestion Client resources within the same resource group so we suggest you create a new resource group.)
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Pick a region. This can be the
same region as your Azure Speech key.
The following settings all relate to the resources and their attributes:
- Give your storage account a name. You will be using a new storage account rather than an existing one.
The following 2 steps are optional. If you omit them, the tool will use the base model to obtain transcripts. If you have created a Speech model, then enter a custom model.
Transcripts are obtained by polling the service. We acknowledge that there is a cost related to that. So, the following setting gives you the option to limit that cost by telling your Azure Function how often you want it to fire.
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Enter the polling frequency. There are many scenarios where this would be required to be done couple of times a day.
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Enter locale of the audio. You need to tell us what language model we need to use to transcribe your audio.
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Enter your Azure Speech subscription key and Locale information.
The rest of the settings relate to the transcription request. You can read more about those in How to use batch transcription.
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Select a profanity option.
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Select a punctuation option.
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Select to Add Diarization [all locales] .
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Select to Add Word level Timestamps [all locales] .
If you want to perform Text Analytics, add those credentials.
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Add Text analytics key
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Add Text analytics region
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Add Sentiment
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Add Personally Identifiable Information (PII) Redaction
NOTE: The ARM template also allows you to customize the PII categories through the PiiCategories variable (e.g., to only redact person names and organizations set the value to "Person,Organization"). A full list of all supported categories can be found in the PII Entity Categories. The ARM template also allows you to set a minimum confidence for redaction through the PiiMinimumPrecision value, the value must be between 0.0 and 1.0. More details can be found in the Pii Detection Documentation.
If you want to further analytics we could map the transcript json we produce to a DB schema.
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Enter SQL DB credential login
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Enter SQL DB credential password
Press Create to create the resources. It typically takes 1-2 mins. The resources are listed below.
If a Consumption Plan (Y1) was selected for the Azure Functions, make sure that the functions are synced with the other resources (see Trigger syncing for further details).
To do so, click on your StartTranscription function in the portal and wait until your function shows up:
Do the same for the FetchTranscription function:
Important: Until you restart both Azure functions you may see errors.
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Upload audio files to the newly created audio-input container.
Use Azure Portal or Microsoft Azure Storage Explorer to upload call audio files to your new storage account in audio-input container. The process of transcription is asynchronous. Transcription usually takes half the time of the audio track to complete. The structure of your newly created storage account will look like the picture below.
There are several containers to distinguish between the various outputs. We suggest (for the sake of keeping things tidy) to follow the pattern and use the audio-input container as the only container for uploading your audio.
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Check results of batch analytics: Once the batch process fiishes, results are added to json-result-output and test-results-output containers in the same storage account.
