https://github.com/waghib/speech-to-text-using-whisper
A web-based audio transcription tool that converts speech to text using OpenAI's Whisper model. Built with Python and Streamlit for easy audio file uploads and accurate transcriptions.
https://github.com/waghib/speech-to-text-using-whisper
openai speech-to-text streamlit whisper-ai
Last synced: about 2 months ago
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A web-based audio transcription tool that converts speech to text using OpenAI's Whisper model. Built with Python and Streamlit for easy audio file uploads and accurate transcriptions.
- Host: GitHub
- URL: https://github.com/waghib/speech-to-text-using-whisper
- Owner: Waghib
- Created: 2025-02-03T18:08:13.000Z (over 1 year ago)
- Default Branch: main
- Last Pushed: 2025-02-04T18:52:58.000Z (over 1 year ago)
- Last Synced: 2025-02-12T12:17:14.885Z (over 1 year ago)
- Topics: openai, speech-to-text, streamlit, whisper-ai
- Language: Python
- Homepage: https://speech2texts.streamlit.app/
- Size: 1 MB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 1
-
Metadata Files:
- Readme: README.md
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README
# 🎙️ AudioScribe
**Transform your audio into text with AI-powered transcription**
[](https://www.python.org/downloads/)
[](https://streamlit.io)
[](https://github.com/openai/whisper)
[](LICENSE)
## 📸 Screenshots
### Upload Screen
*Clean and intuitive interface for audio file upload*
### Transcription Result
*Real-time transcription with audio preview and download options*
## ✨ Features
- 🎯 **High-Accuracy Transcription** using OpenAI's Whisper model
- 🎵 **Multiple Audio Formats** support (MP3, WAV, M4A, OGG)
- 🎧 **Built-in Audio Player** for preview
- 💾 **Instant Download** of transcription results
- 🎨 **Modern, Clean UI** for the best user experience
## 🚀 Quick Start
### Prerequisites
- Python 3.8 or higher
- FFmpeg (required for audio processing)
### Installation
1. Clone the repository:
```bash
git clone https://github.com/yourusername/AudioScribe.git
cd AudioScribe
```
2. Install required packages:
```bash
pip install -r requirements.txt
```
3. Run the application:
```bash
streamlit run main.py
```
The app will be available at `http://localhost:8501`
## 💡 Usage
1. **Upload Audio**
- Click the upload area or drag and drop your audio file
- Supported formats: MP3, WAV, M4A, OGG
- Maximum file size: 200MB
2. **Preview Audio** (Optional)
- Use the built-in audio player to verify your upload
- Check the audio quality before transcription
3. **Get Transcription**
- Wait for the AI model to process your audio
- View the transcribed text in real-time
- Download the results as a text file
## 🛠️ Tech Stack
- **Frontend**: [Streamlit](https://streamlit.io)
- **AI Model**: [OpenAI Whisper](https://github.com/openai/whisper)
- **Audio Processing**: [FFmpeg](https://ffmpeg.org)
- **Python Libraries**:
- `streamlit`: Web application framework
- `whisper`: AI transcription model
- `tempfile`: Temporary file handling
- `datetime`: Timestamp generation
## 📝 License
This project is licensed under the MIT License - see the [LICENSE](LICENSE) file for details.
## 🤝 Contributing
Contributions are welcome! Please feel free to submit a Pull Request.
1. Fork the repository
2. Create your feature branch (`git checkout -b feature/AmazingFeature`)
3. Commit your changes (`git commit -m 'Add some AmazingFeature'`)
4. Push to the branch (`git push origin feature/AmazingFeature`)
5. Open a Pull Request
## 📬 Contact
Your Name - [@website](https://waghib.github.io) - waghibahmad30@gmail.com
Project Link: [https://github.com/Waghib/WhisperAI-Speech-Recognition](https://github.com/Waghib/WhisperAI-Speech-Recognition)
---
Made with ❤️ using OpenAI Whisper and Streamlit