Comments (1)
Hi @JanweiCen ,
As mentioned in the README.md
file, after you clone the repository, you need to first install the requirements:
pip3 install -r requirements.txt
Then open up a new Python file in the current directory and use the codes provided in the examples in the README.md
file. Here is the first example:
from emotion_recognition import EmotionRecognizer
from sklearn.svm import SVC
# init a model, let's use SVC
my_model = SVC()
# pass my model to EmotionRecognizer instance
# and balance the dataset
rec = EmotionRecognizer(model=my_model, emotions=['sad', 'neutral', 'happy'], balance=True, verbose=0)
# train the model
rec.train()
# check the test accuracy for that model
print("Test score:", rec.test_score())
# check the train accuracy for that model
print("Train score:", rec.train_score())
Hope this helps.
Thanks,
from emotion-recognition-using-speech.
Related Issues (20)
- Test without training again HOT 3
- How to do it step by step
- Different Results in Example 2 HOT 1
- Rnn in deep learning usage is problematic in terms of feature space HOT 1
- References paper HOT 1
- Problem with GridSearch HOT 6
- Where the SVC () model is saved? HOT 1
- The relationship between LSTM and classifier HOT 1
- ModuleNotFoundError: No module named 'numba.decorators' HOT 6
- Error while running the pretrained model: No such file or directory: 'train_custom.csv' HOT 5
- I could not run the example in the readme HOT 2
- Error - All the input arrays must have same number of dimensions HOT 1
- SVR parameters commented HOT 3
- ImportError: numpy.core.multiarray failed to import HOT 1
- extract_feature, did not work. HOT 1
- librosa.feature.melspectrogram出错 HOT 1
- Regarding set up of project
- Confusion matrix incomplete problem 混淆矩阵不完整 HOT 1
- RNN Model not predicting
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from emotion-recognition-using-speech.