Urban-Sound-Classification-with-UrbanSound8K-Dataset

🎵 Urban-Sound-Classification-with-UrbanSound8K-Dataset 🔊🤖

Urban-Sound-Classification-with-UrbanSound8K-Dataset is a deep learning project that classifies urban sound events (sirens, drilling, dog barks, street music, etc.) using the UrbanSound8K dataset. It demonstrates how audio signal processing + neural networks can power sound recognition systems for smart cities, surveillance, and real-time monitoring.

✨ Key Features

🎧 Dataset: Uses the UrbanSound8K dataset with 8,732 labeled audio samples across 10 classes

🔊 Audio Preprocessing: MFCCs, Mel-Spectrograms, Chroma features, Feature scaling

🧠 Deep Learning Models: CNN, RNN, LSTM for sound event classification

📊 Model Evaluation: Accuracy, F1-score, Confusion Matrix, ROC-AUC

🖼️ Visualization: Spectrogram plots & feature distribution analysis

⚡ Real-Time Prediction (Optional): Test with microphone input or uploaded audio files

🌐 Deployment: Streamlit / Flask app for live sound classification

🧰 Tech Stack

Programming: Python 🐍

Libraries: Librosa, NumPy, Pandas, Matplotlib, Seaborn

Deep Learning: TensorFlow / Keras, PyTorch

Deployment (Optional): Streamlit / Flask

📁 Project Structure 📁 data/ # UrbanSound8K dataset 📁 notebooks/ # Jupyter notebooks for preprocessing & experiments 📁 src/ # Training & evaluation scripts 📁 models/ # Trained models 📁 results/ # Metrics, confusion matrices, plots 📁 app/ # (Optional) Web app for live sound classification

🚀 Getting Started git clone https://github.com/yourusername/Urban-Sound-Classification-with-UrbanSound8K-Dataset.git cd Urban-Sound-Classification-with-UrbanSound8K-Dataset pip install -r requirements.txt jupyter notebook

📌 Use Cases

🌆 Smart Cities: Noise monitoring & urban soundscape analysis

🚨 Surveillance & Security: Detect alarms, sirens, and unusual sounds

🏥 Healthcare: Assistive devices for the hearing impaired

🎓 Education: Learn audio signal processing & deep learning fundamentals

🤝 Contributing

Contributions are welcome! Improve preprocessing, add new models, or enhance deployment and submit a PR.

📜 License

MIT License – Free for research, education, and personal use.