1. Automated Subtitling and Transcription with AWS MediaLive and AI


    In order to create an automated subtitling and transcription system using AWS services, you would typically employ AWS MediaLive to handle live video streams and AWS Transcribe to convert speech in the video to text. AWS MediaLive is a broadcasting service that allows you to create high-quality video streams for delivery to broadcast televisions and internet-connected multiscreen devices. AWS Transcribe uses deep learning to add accurate and timely captions to your videos, making it a handy tool for creating subtitles.

    The following program demonstrates how to use Pulumi to create a simple setup with AWS MediaLive and AWS Transcribe. The program assumes that you have the necessary media source URLs and will create a MediaLive channel for streaming content and a Transcribe job to transcribe the content of the stream.

    The program will comprise the following steps in Pulumi:

    1. Create a MediaLive channel: This channel will process your input source and compress it into the desired format. Defined by aws.medialive.Channel.

    2. Create a Transcription job: Once the channel is set up, we can feed its output to AWS Transcribe to start transcribing the stream. This is simplified as Pulumi doesn't directly support this integration; it would normally be an operation orchestrated by code using the AWS SDKs, possibly triggered by a notification or another AWS resource, depending on the precise workflow required. For example, you could use AWS Lambda to trigger the transcription job and AWS S3 to store the output.

    Below is the Pulumi program written in Python that demonstrates the first step, which is setting up the AWS MediaLive channel:

    import pulumi import pulumi_aws as aws # Assuming you have the input source set up correctly. # Replace `s3_input_url` with your actual S3 bucket URL or other input URL for your media. s3_input_url = "s3://your-bucket/url-to-your-media-file" # Create an AWS MediaLive input. We're simulating an input here. media_live_input = aws.medialive.Input("mediaInput", type="URL_PULL", sources=[ aws.medialive.InputSourceArgs( url=s3_input_url ) ] ) # Create an AWS MediaLive channel media_live_channel = aws.medialive.Channel("mediaChannel", input_attachments=[ aws.medialive.ChannelInputAttachmentArgs( input_id=media_live_input.id ) ], # The rest of the configuration should be set according to your specific requirements. # The `encoder_settings`, `destinations`, etc., will need to be configured to match your setup. ) # Export the MediaLive channel ID and endpoint so they can be used/referenced outside of Pulumi. pulumi.export('medialive_channel_id', media_live_channel.id) # This endpoint would also need to be configured with your output settings. pulumi.export('medialive_channel_endpoint', media_live_channel.endpoint) # Note: AWS Transcribe integration is not directly available through Pulumi resources # at the time of writing. You would need to utilize AWS SDKs or Lambda functions # triggered by MediaLive events to start transcription jobs.

    Please note that the above script sets up only the AWS MediaLive side of the process. Setting up the AWS Transcribe side would usually be done through an AWS SDK or an orchestration service like AWS Step Functions, because that would involve programmatic steps beyond the scope of infrastructure provisioning (which is what Pulumi is primarily designed for).

    You'd also need AWS IAM roles with the necessary permissions and potentially other resources, depending on your use case. For transcriptions and subtitles, you would typically trigger Transcribe jobs based on outputs from your MediaLive channel, then handle the transcribe job results to generate subtitles in your desired format, potentially combining them with the video and re-uploading to a CDN or hosting service for distribution.

    For detailed references, you can follow the official Pulumi documentation for AWS MediaLive Channel: AWS MediaLive Channel. For automating transcriptions, you would need to refer to the AWS Transcribe documentation: AWS Transcribe Documentation.

    Remember to replace placeholders, such as s3_input_url, with actual values. Also, fill in the remainder of the channel configuration to suit your requirements, which is context-specific and depends on your exact setup and workflows.