Computer Vision & ML
Real-time Emotion Recognition from Audio
CNN-LSTM model trained on RAVDESS dataset for emotion classification, with real-time microphone audio-capture pipeline extracting MFCC, chroma, and mel-spectrogram features.
Key Architectural & System Features
Trained CNN-LSTM model extracting MFCC, chroma, and mel-spectrogram features
Classified 8 emotion classes using Categorical Cross-Entropy loss
Built real-time microphone audio-capture pipeline to predict emotion on the fly
Technologies & Tools Stack
PythonLibrosaCNN/LSTMKaggle RAVDESS Dataset