EsratMaria/Speech_Emotion_Recognition_Model
A speech emotion detection classifier on CREMA dataset. This classifier attempts to recognize human emotion and effective states from speech.
This project helps anyone who needs to automatically identify human emotions like sadness, anger, disgust, neutrality, happiness, or fear from spoken words. It takes audio recordings as input and outputs the detected emotion for each speaker. Call centers, market researchers, or mental health professionals could use this to understand emotional cues.
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Use this if you have audio data and need to automatically categorize the emotional state expressed in the speech.
Not ideal if you need to detect subtle emotional nuances beyond the six core emotions provided, or if your audio quality is very poor.
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Feb 02, 2024
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