A developer is working on building a “Deep Search AI solution” for a video library company.
The solution requires insights extraction from video to improve user video searching experience.
The solution also requires enabling users to “create content for social media” based on the insights from their videos.
Which Azure cognitive service should the developer use?
Click on the arrows to vote for the correct answer
A. B. C. D.Correct Answer: C.
Option A is INCORRECT.
Face API facilitates searching, identifying, and matching faces in a private repository.
These actions could be done for up to 1 million people.
Option B is INCORRECT.
Computer vision helps in real-time video analysis, extraction of text automation, but will not be useful for the given scenario.
Option C is CORRECT.
Video indexer can be used to extract insights from videos and these insights could be used for:
-Deep Search
-Content Creation
-Accessibility
-Monetization
-Recommendations
-Content Moderations Option D is INCORRECT.
Bing Video Search provides functionality to search video across the web and cannot help in building an AI solution as detailed in the scenario.
References:
Based on the given requirements, the Azure cognitive service that best fits the solution is the Video Indexer (option C).
The Video Indexer is a powerful Azure cognitive service that provides various features to extract insights and metadata from videos, including:
Speech-to-Text: It can convert the speech in the video into text, which can be used for searching, tagging, or generating captions.
Face detection: It can recognize faces and identify emotions, which can be useful in determining the mood of the video and improve search results.
Object detection: It can detect objects within the video, such as cars, buildings, or animals, which can be used for tagging and searching.
Scene detection: It can identify different scenes within the video, which can be used to create a summary of the video or enable users to jump to specific scenes.
Keyframe extraction: It can extract keyframes from the video, which can be used as a thumbnail or to summarize the content of the video.
The Video Indexer also offers a range of customization options to fit different use cases, such as custom speech models, custom visual classifiers, and custom entity recognition.
Regarding the second requirement, creating content for social media, the insights extracted from the video can be used to generate captions, hashtags, or summaries that can be shared on social media platforms. This functionality can be achieved by integrating the Video Indexer with other Azure services, such as Azure Functions or Logic Apps, to automate the process of generating social media content based on the video insights.
In conclusion, the Video Indexer is the most suitable Azure cognitive service for building a "Deep Search AI solution" for a video library company, as it provides various features to extract insights and metadata from videos, and can enable users to create content for social media based on these insights.