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| title: English Accent Classifier | |
| emoji: 🗣️ | |
| colorFrom: blue | |
| colorTo: purple | |
| sdk: gradio | |
| sdk_version: 5.30.0 | |
| app_file: app.py | |
| pinned: false | |
| Overview | |
| This web app uses Gradio and Hugging Face Transformers to classify English accents from audio samples. | |
| Upload or record English speech, and the app predicts the speaker’s accent from: | |
| American | |
| British | |
| Indian | |
| African | |
| Australian | |
| Results are displayed in a clear, color-coded table showing confidence percentages, highlighting the top predicted accent. | |
| Demo | |
| Try the live app on Hugging Face Spaces: | |
| https://huggingface.co/spaces/tusker123/accent-detection | |
| Installation | |
| Clone the repo and install dependencies: | |
| bash | |
| git clone https://github.com/your-username/english-accent-classifier.git | |
| cd english-accent-classifier | |
| # Optional: create and activate virtual environment | |
| python -m venv venv | |
| # On Linux/macOS: | |
| source venv/bin/activate | |
| # On Windows: | |
| venv\Scripts\activate | |
| pip install -r requirements.txt | |
| If requirements.txt is not included, install manually: | |
| bash | |
| pip install gradio transformers torch | |
| Running Locally | |
| Start the app: | |
| bash | |
| python app.py | |
| Open the local URL printed (usually http://127.0.0.1:7860) in your browser. | |
| Deploying on Hugging Face Spaces | |
| Create a new Space on Hugging Face using the Gradio SDK. | |
| Upload your app.py and requirements.txt. | |
| Ensure your app.py ends with: | |
| #python | |
| gr.Interface(...).launch() | |
| (Do NOT use share=True on Spaces.) | |
| Commit and wait for the build; your app will be publicly available. | |
| How It Works | |
| Uses the Hugging Face pipeline: | |
| #python | |
| pipeline("audio-classification", model="dima806/english_accents_classification") | |
| Takes an audio input, predicts accents with confidence scores. | |
| Displays top 3 accents in a styled table with the top accent highlighted. | |
| Error Handling | |
| Handles invalid audio files gracefully with user-friendly error messages. | |
| Supports common audio formats like .wav and .mp3. | |
| Customization | |
| Change the model in app.py by editing: | |
| #python | |
| pipe = pipeline("audio-classification", model="your_model_name") | |
| Customize UI elements and theme in the Gradio interface. | |
| License & Acknowledgments | |
| This project leverages open-source libraries: | |
| Gradio | |
| Transformers | |
| Model by dima806 | |
| Contact | |
| For inquiries or support, contact: | |
| duncan.ngacha@gmail.com |