Integrate a custom language model into Azure Video Indexer

Azure Video Indexer is an AI-powered service offered by Microsoft that allows you to extract insights from videos. These insights help in taking strategic decisions and can be used in various applications ranging from content management to accessibility.

Understanding Custom Language Models

A custom language model is a tool to optimize the performance of automatic speech recognition (ASR) systems. These models are designed to understand the unique vocabulary used in specific industries or organizations.

For example, in the medical healthcare industry, a speech recognition system without a custom language model might misinterpret ‘antihistamine’ as ‘anti-histamine’. This makes a significant difference in the context. But when a custom language model trained specifically for the healthcare industry is implemented, such errors can be efficiently avoided.

Integrating a Custom Language Model into Azure Video Indexer

Now, let’s dive into the process of integrating a custom language model into Azure Video Indexer.

Step 1: Create a Custom Language Model

Before integrating, you need to have a custom language model. Azure provides ‘Custom Speech’, a portal to create and manage custom language models.

Step 2: Publishing the Model

Once your language model is trained and ready, you have to publish it. This can be done through the ‘Custom Speech’ portal itself.

Step 3: Getting Model ID

After publishing, you will get a ‘Model ID’. This unique ID will be used to integrate the model with Video Indexer.

Step 4: Integrating the Model into Video Indexer

Finally, integrate your custom language model with Video Indexer by adding the following line of code in every call to Video Indexer API:

“languageModelId”: “Your Model ID”

Just replace ‘Your Model ID’ with the actual model ID you received after publishing the model.

Please note that the dialect code of the custom speech model (e.g., ‘en-US’, ‘fr-FR’, etc.), has to match the language that’s being indexed in the video.

Step 5: Verifying the Integration

After the process is completed, check the ‘Insights’ pane of the video in the Video Indexer. If the model has been integrated correctly, then the speech-to-text transcriptions would reflect the influence of your custom language model.

It’s important to remember that using a custom language model for transcription in Video Indexer doesn’t consume any additional ‘speech-to-text( S2T) hours’. Therefore, it’s a cost-effective way to improve the accuracy of video transcriptions.

Wrapping Up

Integrating a custom language model into Azure Video Indexer can help you significantly enhance your application’s ability to interpret and utilize the video content in a more effective way. By following the steps mentioned above, you can readily integrate a custom language model, sharpen your skills for the AI-102 exam, and ultimately create a more efficient Azure AI solution.

The ability to integrate a custom language model into Video Indexer is an example of the flexibility and extensibility of Azure AI services. This is a key concept for the AI-102 exam and a valuable skill for designing and implementing robust AI solutions.

Remember, practice is the key to mastering these steps and this knowledge will surely give you an edge in the AI-102 exam and in developing innovative AI solutions using Azure Video Indexer.

Practice Test

True or False: Azure Video Indexer supports the integration of custom language models.

• True
• False

Answer: True

Explanation: Azure Video Indexer offers support for custom language models, allowing customization of language recognition capabilities to improve transcription results.

Which of the following is NOT a step in integrating a custom language model into Azure Video Indexer?

• a) Train the language model
• b) Exporting the model and uploading it to Azure Video Indexer
• c) Linking the model to the relevant Video Indexer account
• d) Learning Python to integrate the model

Answer: d) Learning Python to integrate the model

Explanation: While knowledge of a coding language might be useful in general, it is not a direct step in the process of integrating a custom language model into Azure Video Indexer.

True or False: Adaption of Azure Speech to Text language models can be done in Azure Video Indexer.

• True
• False

Answer: True

Explanation: Azure Video Indexer allows the integration of custom language model. This gives the ability to adapt Azure’s Speech to Text language model and achieve improved transcriptions.

True or False: Azure Video Indexer does not require a CRIS endpoint in order to use a custom language model.

• True
• False

Answer: False

Explanation: In order to use a custom language model in Azure Video Indexer, a CRIS (Custom Speech) endpoint is required. This endpoint links the Video Indexer to the custom language model.

Which one is NOT a benefit of integrating a custom language model into Azure Video Indexer?

• a) Improved transcription performance
• b) Support for more languages
• c) Reduced video processing time
• d) Increased costs

Answer: d) Increased costs

Explanation: The main benefits of integrating a custom language model into Azure Video Indexer are improved transcription performance, extended language support and potentially reduced video processing time. However, since the model is custom, it may increase costs.

True or False: Azure Video Indexer can use a custom language model to transcribe and recognize any language, including those not officially supported by Azure.

• True
• False

Answer: False

Explanation: Although a custom language model can improve transcription performance and support additional languages, it cannot recognize languages that are not officially supported by Azure.

For integrating a custom language model into Azure Video Indexer, which of the following information do you need?

• a) CRIS Endpoint
• b) Video Indexer language
• c) Blob storage
• d) Both a) and b)

Answer: d) Both a) and b)

Explanation: For integrating a custom language model, you need a CRIS endpoint where the model resides and the language specified in Video Indexer.

True or False: Video indexer allows integration of custom language models only from Azure’s Speech Services.

• True
• False

Answer: True

Explanation: Azure Video Indexer is designed to integrate with Azure’s Speech Services, which includes the ability to incorporate custom language models.

In the context of Azure Video Indexer, what is CRIS?

• a) Custom Recognition Intelligent Service
• b) Custom Redirection Indexing Service
• c) Custom Recognition Indexing Service
• d) Custom Redirection Intelligent Service

Answer: a) Custom Recognition Intelligent Service

Explanation: In the context of Azure Video Indexer, CRIS stands for Custom Recognition Intelligent Service. It is used to generate a custom endpoint for speech services.

True or False: You can use a custom language model in Azure Video Indexer without training it first.

• True
• False

Answer: False

Explanation: A custom language model needs to be trained with relevant data before it can be integrated into Azure Video Indexer and used to analyze videos.

Interview Questions

What is Azure Video Indexer?

Azure Video Indexer is a cloud-based service that empowers you to extract the insights from videos using artificial intelligence technologies. It provides powerful capabilities such as facial detection, speech-to-text, speaker separation, emotion recognition, and more.

What is the role of a custom language model in Azure Video Indexer?

A custom language model improves the transcription accuracy of the Video Indexer by training it on domain-specific terminology. This is especially useful when dealing with industry-specific jargon, acronyms, or names that are not commonly found in the general language model.

How can you integrate a custom language model into Azure Video Indexer?

You can integrate a custom language model into Azure Video Indexer by integrating it with the Azure Custom Speech portal. You would need to create a custom model, train it with your specific terms, and then use its deployment ID in your Video Indexer API calls.

This custom model integration, does it support multiple languages?

Yes, Azure Video Indexer supports a custom model for each language that’s supported by the Microsoft’s Speech Service custom speech model.

What is the working process of the Video Indexer with a custom language model?

When an indexing request is made with a custom language model ID, the Video Indexer uses the specified model to transcribe the audio. This process significantly enhances the recognition of specific terminology or phrases that are not in the standard language model.

Which endpoint should be used in Video Indexer API to use a custom model?

To use a custom model with Azure Video Indexer, you must specify the model’s deployment ID in the Index video API request. The parameter to specify is called ‘languageModelId’.

How do you ensure that your custom language model is used by Azure Video Indexer?

Once the model has been created and trained in the Custom Speech portal, the deployment ID should be used in the ‘languageModelId’ field when indexing videos in Azure Video Indexer to ensure the custom model is used for the transcription.

Is it possible to utilize multiple custom language models at once during the video indexing process?

No, only one custom language model can be used for each video indexing request. However, different videos may use different custom language models if necessary.

Can you integrate a custom language model into Video Indexer using Video Indexer Portal?

No, currently integrating a custom language model into Video Indexer can only be done via the API. The Video Indexer Portal doesn’t provide this functionality.

How are the results of the Video Indexer affected by using a custom language model?

By using a custom language model, the transcription accuracy of the content can be significantly improved. The enhanced recognition of domain-specific words leads to more valuable insights and metadata extracted from the video content.

What are the prerequisites for integrating a custom language model with the Azure Video Indexer?

You need access to the Azure Custom Speech service portal to create and train your custom language model. Also, you need the deployment ID of your trained model to integrate it with the Azure Video Indexer API.

How does Video Indexer authenticate the use of a custom language model?

Video Indexer uses the same region and subscription authentication as the Custom Speech service, therefore you need to ensure that your Video Indexer account and your Custom Speech service are in the same Azure region and subscription.

Can custom language models be used in the Azure Government region?

Yes, custom language models are available in the Azure Government region by accessing Azure Video Indexer through the Government API endpoint.

How to update an existing custom language model in Video Indexer?

To update an existing custom language model, you need to retrain the model with new data in the Azure Custom Speech service portal and update the ‘languageModelId’ in the Video Indexer API with the new deployment ID.

How much does it cost to use a custom language model in Video Indexer?

Charges for custom language models are separate from Video Indexer and billed under Azure Speech Services. Please refer to the pricing details on the Azure website for detailed cost information. Video Indexer itself does not add any charges for using a custom language model.