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# [How to Make a Speech Emotion Recognizer Using Python And Scikit-learn](https://www.thepythoncode.com/article/building-a-speech-emotion-recognizer-using-sklearn)
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To run this, you need to:
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-`pip3 install -r requirements.txt`
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It is already trained, you can use `test.py` to test your voice.
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You can:
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- Tweak the model parameters ( or the whole model ) in `ser.py`.
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- Add more data to `data` folder in condition that the audio samples are converted to 16000Hz sample rate and mono channel, `convert_wavs.py` does that.
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- Editing the emotions specified in `utils.py` in `AVAILABLE_EMOTIONS` constant.
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When you modified anything, you can run `ser.py` to retrain the model.
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If you want to only use this efficiently, definitely check [Emotion Recognition using Speech](https://github.com/x4nth055/emotion-recognition-using-speech) repository which ease this process a lot.
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