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| title: English Dialect Classifier | |
| emoji: 🚀 | |
| colorFrom: red | |
| colorTo: red | |
| sdk: streamlit | |
| app_file: app.py | |
| app_port: 8501 | |
| tags: | |
| - streamlit | |
| pinned: false | |
| short_description: Predicting English Dialect Using Speech Brain and Streamlit | |
| license: apache-2.0 | |
| # Welcome to Streamlit! | |
| Edit `/src/streamlit_app.py` to customize this app to your heart's desire. :heart: | |
| If you have any questions, checkout our [documentation](https://docs.streamlit.io) and [community | |
| forums](https://discuss.streamlit.io). | |
| 🎤 English Accent Analyzer | |
| Streamlit App | |
| PyTorch | |
| A tool to identify English accents from audio/video sources with optimized processing for large files. | |
| 🚀 Features | |
| Supports local files, direct media URLs, and Loom videos | |
| Automatically splits large files into 1-minute chunks | |
| Early stopping for faster analysis | |
| Confidence-based predictions | |
| Interactive Streamlit dashboard | |
| ⚙️ Installation | |
| Clone the repository: | |
| bash | |
| git clone https://github.com/your-username/accent-analyzer.git | |
| cd accent-analyzer | |
| Install dependencies: | |
| bash | |
| pip install -r requirements.txt | |
| Install FFmpeg (required for audio processing): | |
| bash | |
| # On Ubuntu/Debian | |
| sudo apt install ffmpeg | |
| # On macOS | |
| brew install ffmpeg | |
| 🖥️ Usage | |
| Run the Streamlit app: | |
| bash | |
| streamlit run app.py | |
| The app will open in your browser at http://localhost:8501 | |
| 📥 Input Options | |
| 1. Upload a file | |
| Supported formats: | |
| Video: .mp4, .webm, .avi, .mov, .mkv, .m4v | |
| Audio: .mp3, .wav, .m4a, .aac, .ogg, .flac | |
| 2. Provide a URL | |
| Loom videos: https://www.loom.com/share/... | |
| Direct media links: https://example.com/video.mp4 | |
| 🔧 Optimizations for Large Files | |
| The system automatically handles large files using these techniques: | |
| Diagram | |
| Code | |
| Chunk Processing: | |
| Audio is split into 1-minute segments | |
| Only segments >10 seconds are processed | |
| Enables parallel processing (future implementation) | |
| Early Stopping: | |
| Stops processing when 3 consecutive chunks agree with high confidence | |
| Saves processing time for long files | |
| Efficient Extraction: | |
| Uses FFmpeg for fast audio extraction | |
| Torchaudio fallback for compatibility | |
| Direct streaming for URL sources | |
| Confidence Threshold: | |
| Only predictions >60% confidence are considered | |
| Reduces false positives from noisy segments | |
| 📊 Example Output | |
| Example Dashboard | |
| The dashboard shows: | |
| Predicted accent with confidence percentage | |
| Confidence scores per minute | |
| Accent distribution charts | |
| Processing time metrics |