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mfcc-analysis

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billy-enrizky / Speech-Emotion-Recognition

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This project focuses on real-time Speech Emotion Recognition (SER) using the "ravdess-emotional-speech-audio" dataset. Leveraging essential libraries and Long Short-Term Memory (LSTM) networks, it processes diverse emotional states expressed in 1440 audio files. Professional actors ensure controlled representation, with 24 actors contributing

deep-learning speech-recognition lstm-neural-networks emotion-recognition mfcc-analysis streamlit ravdess-dataset
  • Updated Jan 4, 2024
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