The S3 Auto-transcriber and sentiment analyzer will automatically convert uploaded MP3 files into transcribed text, using Amazon Transcribe. The resulting text is used to run a sentiment analysis with AWS Comprehend, and then store the result in DynamoDB.
Important: this application uses various AWS services and there are costs associated with these services after the Free Tier usage - please see the AWS Pricing page for details. You are responsible for any AWS costs incurred. No warranty is implied in this example.
This code was originally presented at re:Invent 2019, session ID SVS214.
.
├── README.MD <-- This instructions file
├── sentimentFunction <-- Source code for a lambda function
│ └── app.js <-- Main Lambda handler
│ └── s3.js <-- S3 helper functions
│ └── package.json <-- NodeJS dependencies and scripts
├── transcribeFunction <-- Source code for a lambda function
│ └── app.js <-- Main Lambda handler
│ └── package.json <-- NodeJS dependencies and scripts
├── template.yaml <-- SAM template- AWS CLI already configured with Administrator permission
- NodeJS 12.x installed
-
Create an AWS account if you do not already have one and login.
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From the command line, run:
sam build
sam deploy --template-file packaged.yaml --capabilities CAPABILITY_IAM --stack-name auto-transcriber --region <<enter your region>> --parameter-overrides InputBucketName=<<enter translation bucket name>>
- InputBucketName: the unique name of a new S3 bucket for this application (bucket names must be lowercase only and globally unique across AWS)
- Upload an MP3 file of a person speaking (ending in the suffix '.mp3') to the target S3 bucket.
- After a few seconds you will see a transcription file in the same bucket (using the same object name with .json appended).
- This triggers a sentiment analysis with Amazon Comprehend and the result is stored in an Amazon DynamoDB table.
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Copyright 2020 Amazon.com, Inc. or its affiliates. All Rights Reserved.
SPDX-License-Identifier: MIT-0