Speech Emotion Recognition using RAVDESS Dataset 🎙️😃😢😡

This project is a Speech Emotion Recognition (SER) system that uses machine learning and audio signal processing techniques to classify emotions from speech audio. It leverages the RAVDESS dataset, and includes preprocessing using librosa, followed by training a deep learning model for emotion classification.

🔍 Overview

• Dataset: RAVDESS
• Audio Preprocessing: Feature extraction using librosa (MFCCs, Chroma, Mel spectrogram, etc.)
• Model Architecture: Deep learning model (likely CNN/LSTM-based) built using TensorFlow/Keras
• Emotions Detected: Neutral, Calm, Happy, Sad, Angry, Fearful, Disgust, Surprised

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📁 Project Structure

├── app.ipynb         # Preprocessing script: loading audio, feature extraction using librosa
├── model.ipynb       # Model training: defining, compiling, and training the deep learning model
├── README.md         # Project overview and instructions (this file)