AI-102 Question 162
Select 3A company wants to analyze customer sentiment and identify key topics from their webinar recordings. They plan to use Azure AI Video Indexer. Which steps should they take to extract meaningful insights from the videos?
- A
Upload the video to Azure AI Video Indexer and enable transcription and sentiment analysis during indexing.
- B
Use the Azure AI Video Indexer API to retrieve the sentiment and key topics metadata after processing.
- C
Manually timestamp the video to mark important sections for analysis before uploading.
- D
Enable face detection and speaker identification features to enhance video indexing insights.
- E
Download the raw video file and process it with a custom machine learning model for sentiment analysis.
Show answer and explanation
Correct answers: A, B, D
Explanation
To extract meaningful insights using Azure AI Video Indexer, you need to first upload the video and enable relevant features like transcription and sentiment analysis. After processing, the Video Indexer API can be used to retrieve metadata such as sentiment scores and key topics. Enabling additional features like face detection and speaker identification can further enhance the insights extracted from the video. Manual timestamping and external ML models are not required, as Azure AI Video Indexer provides built-in capabilities for these tasks.
- A. Correct.
Correct: Azure AI Video Indexer allows you to upload videos and enable transcription and sentiment analysis during the indexing process to generate insights.
- B. Correct.
Correct: The Azure AI Video Indexer API provides access to metadata, including sentiment scores and key topics, after the video has been processed.
- C. Incorrect.
Incorrect: Azure AI Video Indexer automatically identifies timestamps and key moments in the video. Manual timestamping is not required.
- D. Correct.
Correct: Enabling features like face detection and speaker identification can provide additional insights and context to the indexed video.
- E. Incorrect.
Incorrect: While custom ML models can be used, Azure AI Video Indexer provides built-in capabilities for sentiment analysis and topic extraction, making this step unnecessary in this context.