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