Shypd.aiThe largest open index of AI toolsSpeech-Emotion-Recognition is an open-source AI tool that detects emotions in speech using machine learning models like LSTM, CNN, SVM, and MLP. It offers improved feature extraction, achieving approximately 80% accuracy.
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Speech-Emotion-Recognition is an open-source project designed for identifying emotions in spoken language. It leverages various machine learning models, including Long Short-Term Memory (LSTM), Convolutional Neural Networks (CNN), Support Vector Machines (SVM), and Multilayer Perceptrons (MLP), all implemented within the Keras framework. The tool focuses on advanced feature extraction techniques, which contribute to its reported accuracy of around 80%. It supports Python and integrates with essential libraries such as scikit-learn for model training and evaluation, and librosa for audio feature processing. This makes it a valuable resource for researchers and developers working on speech analysis and emotion detection applications.
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