Comments (3)
I haven't changed anything in the code. I have written some scripts for my own usage. The program works fine for the provided .wav files in the data sets. However, in my case, the program terminates without any prediction or probability score being printed in the console.
from emotion-recognition-using-speech.
Hi @maximtolea ,
Before using any outsider audio file, you need to first convert its sample rate to 16000Hz and mono channel, I've provided the script create_wavs.py
for that case. Note that you'll need to have ffmpeg
installed in your machine in order to properly convert the audio files.
Hope this helps. Let me know when this solves your issue.
from emotion-recognition-using-speech.
Hey again,
I've updated the code to automatically convert to the appropriate format when using the predict()
method. Pull the repo again and check it out!
Thanks, closing the issue.
from emotion-recognition-using-speech.
Related Issues (20)
- Speech to text problem HOT 1
- Error while running the pretrained model: No such file or directory: 'train_custom.csv' HOT 4
- Test without training again HOT 3
- How to do it step by step
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- 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
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- 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
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from emotion-recognition-using-speech.