Analysis workflow
The analysis workflow includes AWS Step Functions and AWS Lambda which leverage Amazon Rekognition, Amazon Transcribe, Amazon Comprehend, and Amazon Textract to analyze and extract machine learning metadata from the proxy files generated in the ingestion workflow. The Media2Cloud on AWS solution provides the following preset options for the analysis process when you deploy the template: Default, All, and Audio and Text.
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Default - Activates celebrity recognition, labels, transcription, key phrases, entities, and text processes.
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All - Activates all detections including celebrity recognition, labels, transcription, key phrases, entities, text, faces, face matches, person, moderation, sentiment, and topic processes.
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Audio and Text - Activates transcription, key phrases, entities, and text processes.
The web interface also allows the end user to refine the AI/ML settings during the upload process.
The analysis workflow includes four sub-state machines to process the analysis.
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The video analysis state machine analyzes and extracts AI/ML metadata from the video proxy using Amazon Rekognition video APIs.
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The audio analysis state machine analyzes and extracts AI/ML metadata from the audio stream of the proxy file using Amazon Transcribe and Amazon Comprehend.
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The image analysis state machine analyzes and extracts image metadata with Amazon Rekognition image APIs.
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The document analysis state machine extracts text, images, and data using Amazon Textract.
To start the analysis workflow, a Lambda function first checks an incoming analysis
request and prepares the optimal AI/ML analysis option to run, based on the type of media in
the request, and the availability of specific detections. For video and audio, it transforms
the metadata results into WebVTT subtitle tracks, chapter markers, key phrases, labels,
sentiments, entities, and locations. The analysis workflow can also provide customized
analysis output if the customer uses Amazon Rekognition custom label models

Media2Cloud on AWS analysis workflow