https://github.com/kushxkalsi/video-audio-summarization-app
The Video/Audio Summarization Application transcribes and summarizes lengthy audio or video files, helping users quickly access key information. Using Wav2Vec 2.0 for accurate transcription and a summarization model, it provides concise, digestible summaries. With a user-friendly interface, it's suitable for both academic and professional use.
https://github.com/kushxkalsi/video-audio-summarization-app
deeo-learning python stream summarization
Last synced: about 2 months ago
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The Video/Audio Summarization Application transcribes and summarizes lengthy audio or video files, helping users quickly access key information. Using Wav2Vec 2.0 for accurate transcription and a summarization model, it provides concise, digestible summaries. With a user-friendly interface, it's suitable for both academic and professional use.
- Host: GitHub
- URL: https://github.com/kushxkalsi/video-audio-summarization-app
- Owner: KushxKalsi
- Created: 2024-10-28T05:26:30.000Z (over 1 year ago)
- Default Branch: main
- Last Pushed: 2025-08-14T04:51:46.000Z (10 months ago)
- Last Synced: 2025-08-22T20:08:47.578Z (10 months ago)
- Topics: deeo-learning, python, stream, summarization
- Language: Jupyter Notebook
- Homepage:
- Size: 15.6 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# Video/Audio Summarization Application
A Python-based Streamlit **Video/Audio Summarization Application** that allows users to upload audio or video files, transcribe the content, and generate concise summaries for easy reference.
## Features
- Upload and process video/audio files for transcription
- Automatic transcription of audio content using Wav2Vec 2.0
- Summarize lengthy transcriptions into brief, digestible content
- User-friendly interface with real-time processing and feedback
## Screenshots
Home Screen
Transcription Output
Summary Output
## Installation
1. Clone the repository:
```bash
git clone https://github.com/yourusername/VideoAudioSummarizationApp.git
cd VideoAudioSummarizationApp
```
2. Install dependencies:
```bash
pip install -r requirements.txt
```
3. Run the Streamlit app:
```bash
streamlit run app.py
```
## Usage
1. Open the application in your browser (typically at `http://localhost:8501`).
2. Upload a video or audio file in **.mp4**, **.wav**, or **.mp3** format.
3. The app will extract audio (if a video file is uploaded), transcribe it, and display the transcription.
4. View the summarized content in the Summary section.
## Adding Audio/Video Samples to GitHub
To add sample audio or video files to GitHub:
1. Place sample files in a directory within the project, such as `sample_files/`.
2. In your README, provide links to these files for easy access.
3. Use these sample files for demo purposes or to facilitate testing and contributions.
## Built With
- [Python](https://www.python.org/) - The programming language used.
- [Streamlit](https://streamlit.io/) - For the interactive web application.
- [Hugging Face Transformers](https://huggingface.co/) - For speech-to-text and summarization models.
- [Librosa](https://librosa.org/) - For audio processing.
## Contributing
Contributions are welcome! To contribute, please submit a pull request and follow the standard GitHub workflow.
## Acknowledgments
- Hugging Face community for providing state-of-the-art NLP models.
- Inspiration from various NLP resources for implementing the summarization feature.
## Author
Kush Kalsi