Spaces:
Sleeping
Sleeping
| title: Trascriber | |
| emoji: 📜 | |
| colorFrom: blue | |
| colorTo: blue | |
| sdk: streamlit | |
| sdk_version: "1.40.2" | |
| app_file: app.py | |
| pinned: true | |
| # YouTube Video Transcriber | |
| A Streamlit app that transcribes YouTube videos using Whisper, with optional formatting using a large language model, audio download, and video download. | |
| ## How it works | |
| - Downloads audio from YouTube videos using `yt-dlp`. | |
| - Splits audio into speech segments using Silero VAD. | |
| - Transcribes segments in batches using OpenAI's Whisper model. | |
| - Formats the transcription using a large language model (if selected). | |
| - Displays transcribed text with timestamps. | |
| - Provides options to download the raw transcription, formatted transcription, audio, or video. | |
| ## Requirements | |
| Listed in `requirements.txt` | |
| ## Usage | |
| 1. Install dependencies: `pip install -r requirements.txt` | |
| 2. Run the app: `streamlit run app.py` | |
| 3. Enter a YouTube video URL. | |
| 4. Choose options: Transcribe, Download Audio, Download Video, Format Text. | |
| 5. Select a language or use auto-detect (under "Advanced Settings"). | |
| 6. Click "Process". | |
| ## Screenshot | |
|  | |
| ## License | |
| MIT | |