Document Processing and Speech API

A TypeScript-based Express API for document processing (PDF/DOCX), speech-to-text, and text-to-speech conversion using Google Cloud services.

Features

• 📄 Document Processing (PDF & DOCX)
• 🎤 Speech to Text Conversion
• 🔊 Text to Speech Conversion
• ⚡ Rate Limiting
• 🔒 Type Safety
• 📝 Standardized API Responses

Prerequisites

• Node.js (v14 or higher)
• TypeScript (v4 or higher)
• Google Cloud Account with Speech & Text-to-Speech APIs enabled
• Service Account Key from Google Cloud

Installation

1. Clone the repository:

git clone <repository-url>
cd document-speech-api

2. Install dependencies:

npm install

3. Set up environment variables: Create a .env file in the root directory:

PORT=3000
GOOGLE_APPLICATION_CREDENTIALS="path/to/your/service-account-key.json"
RATE_LIMIT_WINDOW_MS=900000
RATE_LIMIT_MAX_REQUESTS=100

Project Structure

src/
├── controllers/
│   ├── documentReaderController.ts
│   ├── speechToTextController.ts
│   └── textToSpeechController.ts
├── services/
│   ├── documentReaderService.ts
│   ├── speechToTextService.ts
│   └── textToSpeechService.ts
├── routes/
│   └── apiRoutes.ts
├── types/
│   ├── express.d.ts
│   └── api_response.ts
├── utils/
|   ├── api_response.ts
│   └── logger.ts
├── middlewares/
|   ├── errorHandlerMiddleware.ts
│   └── rateLimitMiddleware.ts
├── app.ts
└── server.ts

Dependencies

{
  "dependencies": {
    "@google-cloud/speech": "^latest",
    "@google-cloud/text-to-speech": "^latest",
    "express": "^latest",
    "multer": "^latest",
    "pdf-parse": "^latest",
    "mammoth": "^latest",
    "express-rate-limit": "^latest",
    "dotenv": "^latest"
  },
  "devDependencies": {
    "@types/express": "^latest",
    "@types/multer": "^latest",
    "@types/node": "^latest",
    "typescript": "^latest",
    "ts-node": "^latest",
    "nodemon": "^latest"
  }
}

API Endpoints

1. Document Reading

POST /api/read-document
Content-Type: multipart/form-data

Request

• file: PDF or DOCX file

Response

{
  "code": 0,
  "status": "success",
  "message": "Document read successfully",
  "data": {
    "text": "extracted text content",
    "fileName": "document.pdf",
    "fileType": "application/pdf"
  }
}

2. Speech to Text

POST /api/speech-to-text
Content-Type: multipart/form-data

Request

• audio: Audio file (MP3)

Response

{
  "code": 0,
  "status": "success",
  "message": "Audio transcribed successfully",
  "data": {
    "text": "transcribed text",
    "audioFileName": "audio.mp3",
    "duration": 10.5
  }
}

3. Text to Speech

POST /api/text-to-speech
Content-Type: application/json

Request

{
  "text": "Text to convert to speech",
  "voice": "en-US",  // optional
  "speed": 1.0       // optional
}

Response

• Audio stream (audio/mpeg) if successful
• Error response if failed:

{
  "code": 1,
  "status": "error",
  "message": "Error message"
}

Error Codes

• 0: Success
• 400: Bad Request
• 401: Unauthorized
• 403: Forbidden
• 404: Not Found
• 500: Internal Server Error

Usage Examples

Using axios

import axios from 'axios';

// Document Reading
const readDocument = async (file: File) => {
  const formData = new FormData();
  formData.append('file', file);
  
  try {
    const response = await axios.post('/api/read-document', formData, {
      headers: {
        'Content-Type': 'multipart/form-data'
      }
    });
    return response.data;
  } catch (error) {
    console.error('Error reading document:', error);
    throw error;
  }
};

// Speech to Text
const convertSpeechToText = async (audioFile: File) => {
  const formData = new FormData();
  formData.append('audio', audioFile);
  
  try {
    const response = await axios.post('/api/speech-to-text', formData, {
      headers: {
        'Content-Type': 'multipart/form-data'
      }
    });
    return response.data;
  } catch (error) {
    console.error('Error converting speech to text:', error);
    throw error;
  }
};

// Text to Speech
const convertTextToSpeech = async (text: string) => {
  try {
    const response = await axios.post('/api/text-to-speech', 
      { text },
      { responseType: 'blob' }
    );
    return response.data;
  } catch (error) {
    console.error('Error converting text to speech:', error);
    throw error;
  }
};

Running the Application

1. Development mode:

npm run dev

2. Production mode:

npm run build
npm start

Setting Up Google Cloud Credentials

1. Create a project in Google Cloud Console
2. Enable Speech-to-Text and Text-to-Speech APIs
3. Create a service account and download the key file
4. Set the path to your key file in the GOOGLE_APPLICATION_CREDENTIALS environment variable

Rate Limiting

The API includes rate limiting to prevent abuse. Default settings:

• 100 requests per 15 minutes window
• Customize these values in the .env file

Contributing

1. Fork the repository
2. Create your feature branch (git checkout -b feature/amazing-feature)
3. Commit your changes (git commit -m 'Add some amazing feature')
4. Push to the branch (git push origin feature/amazing-feature)
5. Open a Pull Request

License

This project is licensed under the MIT License - see the LICENSE file for details.