For this project, the dataset of Persian speech recordings with emotional annotations, 'SHEMO-Persian Speech Emotion Detection Database', was utilized. This dataset is publicly available on Kaggle(https://www.kaggle.com/datasets/mansourehk/shemo-persian-speech-emotion-detection-database)
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This project preprocesses a Persian speech emotion detection dataset, extracting and padding MFCC features from audio files. It uses an LSTM model to classify emotions, evaluating performance with metrics such as accuracy, precision, recall, and F1-score.
zahrasafdari/Audio_Sentiment_Classification
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This project preprocesses a Persian speech emotion detection dataset, extracting and padding MFCC features from audio files. It uses an LSTM model to classify emotions, evaluating performance with metrics such as accuracy, precision, recall, and F1-score.
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