Polyphonic – AI Text-to-Speech Converter

🎯 Purpose

Text-to-speech conversion system using Amazon Polly that transforms written content into natural-sounding audio with customizable voice parameters, enabling accessibility and audio content creation.

🏗️ Architecture

• Amazon Polly – Neural text-to-speech engine
• AWS Lambda – Serverless processing function
• Amazon S3 – Input text and output audio storage
• IAM – Secure service permissions

⚙️ Technical Implementation

IAM Configuration

Created role with required permissions:

• AmazonPollyFullAccess
• AmazonS3FullAccess
• AWSLambdaBasicExecutionRole

Lambda Function

Implemented serverless processing using JavaScript:

// Initialize AWS services
const AWS = require('aws-sdk');
const Polly = new AWS.Polly();
const S3 = new AWS.S3();

// Convert text to speech
const params = {
  Text: inputText,
  OutputFormat: 'mp3',
  VoiceId: 'Joanna',
  Engine: 'neural'
};

// Upload to S3
const audioStream = await Polly.synthesizeSpeech(params);
await S3.putObject({
  Bucket: bucketName,
  Key: `audio/${timestamp}.mp3`,
  Body: audioStream.AudioStream
});

System Architecture

Process Flow:

1. Text uploaded to S3 bucket
2. Lambda function triggered
3. Polly converts text to speech
4. Audio file stored in S3
5. Download link generated

🎯 Key Features

• ✅ Neural text-to-speech conversion
• ✅ Multiple voice options (Joanna, Matthew, etc.)
• ✅ Adjustable pitch and speed parameters
• ✅ MP3 audio output format
• ✅ Serverless architecture for scalability

📊 Configuration Options

Voice Parameters

• Voice: Joanna (neural engine)
• Speed: Adjustable (0.25x - 4x)
• Pitch: Customizable range
• Format: MP3, OGG, PCM

Use Cases

• Accessibility features for visually impaired users
• Audiobook creation from text content
• Voice-over generation for videos
• Podcast automation from written scripts
• E-learning content narration

🔧 Technical Highlights

• Event-driven serverless architecture
• Neural TTS engine for natural speech
• S3 integration for scalable storage
• IAM least-privilege security model
• Lambda function optimization for performance

📈 Performance Metrics

• Processing Speed: ~1-2 seconds per paragraph
• Audio Quality: 24kHz neural voices
• Cost Efficiency: Pay-per-character pricing
• Scalability: Handles concurrent requests automatically

🔒 Security Implementation

• IAM role-based access control
• S3 bucket policies for data protection
• Lambda execution role isolation
• Secure credential management

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Built with: Amazon Polly | AWS Lambda | S3 | IAM | JavaScript

Tags: aws polly text-to-speech lambda s3 serverless accessibility audio