The library is useful for analyzing the emotions present in any audio file(call/music/recordings) into three classes namely positive, negative, neutral.
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Updated
Jul 26, 2016 - Python
The library is useful for analyzing the emotions present in any audio file(call/music/recordings) into three classes namely positive, negative, neutral.
Directly from voice, recognise speaker emotion, intensity, & sentiment in speaker utterances.
This is an audio classifier which will classify the audio into two categories - neutral and angry. Used CNN classifier to train the model.
In this project we classify negative audio emotions , data is combined between ( RAVDESS/ SAVEE/TESS and CREMA-D)
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