Urban-Sound-Classification-with-UrbanSound8K-Dataset

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Urban-Sound-Classification-with-UrbanSound8K-Dataset

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🕌 Urban 🚃 Sound 🚋 Classification 🚞 with ⛩ UrbanSound8K 🚁 Dataset is 🛳 a deep 🚠 learning 🚢 that ✈ classifies 🚀 urban 🛼 sound ⛱ events 🚈 the 🚂 UrbanSound8K 🚋 dataset 🏛 demonstrates 🏘 how 🧱 audio 🧸 signal 🏆 processing ⚽ neural 🏀 networks 🥎 can ⚾ power 🏐 sound 🎮 recognition 📟 systems 🔋smart 🧰 cities 💣 surveillance 🪣

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🎵 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.

Urban-Sound-Classification-with-UrbanSound8K-Dataset

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