🎯 Armenian Audio Transcription – Complete Guide

🚀 Running the Project

Terminal 1 – Backend:

cd backend
npm run dev

The server will run at http://localhost:3001

Terminal 2 – Frontend:

cd frontend  
npm start

The app will open at http://localhost:3000

🔑 Getting an OpenAI API Key

1. Sign up at https://platform.openai.com/
2. Go to API Keys: https://platform.openai.com/api-keys
3. Create a new key
4. Add it to the backend/.env file:

OPENAI_API_KEY=sk-your-real-key-here

⚠️ Important: Make sure your OpenAI account has available credits!

📱 Using the App

1. Open http://localhost:3000
2. Drag and drop an audio file into the upload area or click “Choose File”
3. Supported formats: MP3, WAV, OGG, FLAC, M4A, WEBM
4. Maximum file size: 25MB
5. Click “Transcribe Audio”
6. Wait for the result and copy the text

🛠️ Troubleshooting

CORS ошибки:

Make sure the backend runs on port 3001 and the frontend on 3000.

Installation Issues:

# Clear npm cache
npm cache clean --force

# Reinstall dependencies
rm -rf node_modules package-lock.json
npm install

OpenAI API Issues:

• Check your API key in the .env file
• Make sure your account has credits
• Check quotas and limits

File Upload Errors:

• Verify the file format (MP3, WAV, OGG, etc.)
• Ensure the file size does not exceed 25MB
• Check permissions for the uploads folder

🌟 Additional Options

Alternatives to OpenAI API:

1. AssemblyAI:

npm install assemblyai

2. Azure Speech Services:

npm install microsoft-cognitiveservices-speech-sdk

3. Google Cloud Speech:

npm install @google-cloud/speech

Local Whisper (Python):

pip install openai-whisper

Create a file whisper_local.py:

import whisper
import sys

model = whisper.load_model("base")
result = model.transcribe(sys.argv[1], language="hy")
print(result["text"])