Developing a Text Narrator

Using Amazon Polly
Project Overview
The objective of this project is to convert text into natural-sounding speech using Amazon Polly, a cloud-based text-to-speech service. While speech-to-text (STT) is widely recognized and integrated into modern devices, text-to-speech (TTS) plays an equally significant role—though it is often overlooked.TTS technology is widely used across digital content creation, from narrated videos and short-form media to audiobooks and automated voice assistants. It is also a critical tool for accessibility, providing visually impaired individuals with a way to consume written content. Additionally, businesses leverage TTS for customer service automation, interactive voice response (IVR) systems, and localized multilingual communication.By leveraging Amazon Polly, organizations can integrate cost-effective, scalable, and customizable speech synthesis into their applications, enhancing user engagement and accessibility.
Sequence
  • Creating an IAM role
  • Creating an S3 Bucket
  • Writing Lambda function code
  • Checking the output of Amazon Polly
text-to-speech AWS diagram

To enable Lambda to execute the necessary tasks, I first attached the required IAM roles via the IAM console: AmazonPollyFullAccess, AmazonS3FullAccess, AWSLambdaBasicExecutionRole

Step 1: Assign IAM roles for lambda Execution

To enable Lambda to execute the necessary tasks, I first attached the required IAM roles via the IAM console: AmazonPollyFullAccess, AmazonS3FullAccess, AWSLambdaBasicExecutionRole

  • I created an S3 bucket where the converted speech files will be stored.
  • I named the bucket "speech-converted-files" and kept the default configurations.
Step 2: Create an S3 Bucket for Storing Converted Speech
  • In the AWS Lambda console, I created a new Lambda function and assigned it the IAM roles from Step 1.
    ‍
    Named the function appropriately.
    Chose Node.js as the runtime.
    Selected "Use an existing role".
  • Edited the index.mjs file to implement text-to-speech conversion using Amazon Pollyand storage in S3:

    Renamed index.mjs to index.js.
    Inserted the appropriate code for Lambda execution.
    Deployed the updated code.
Step 3: Create and Configure the Lambda Function
  • Created a test event in Lambda and input the text I wanted to convert.
  • Executed the test event to verify the function's performance.
  • Upon successful execution, the converted speech file was generated and stored in the S3 bucket.
Step 4: Test the Text-to-Speech Conversion
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