Shypd.aiThe largest open index of AI toolsSpeech-Emotion-Analyzer is an open-source neural network model that detects five different male/female emotions from audio speeches. It is built using deep learning, NLP, and Python.
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Speech-Emotion-Analyzer is an open-source project designed to build a machine learning model capable of detecting emotions from speech. The neural network model can identify five different male/female emotions from audio speeches, leveraging deep learning, natural language processing (NLP), and Python. The project utilizes datasets like RAVDESS and SAVEE for training, extracting features using the LibROSA library. While Multilayer Perceptrons and Long Short Term Memory models were explored, a Convolutional Neural Network proved most effective, achieving over 70% accuracy in emotion detection and 100% accuracy in distinguishing male/female voices. This tool has potential applications in various industries, such as marketing for personalized product recommendations or automotive for adjusting autonomous car behavior based on driver emotion.
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