live demo about speech-emotion-analyzer

[torrentillo]

ataya have you got the 70% accuracy with this model?

[MiteshPuthran]

Hello @Ataya95, you have not loaded the saved model before running this code. See cell no 137 where the model is loaded and then used in the live demo.

[Ataya95]

Solved
Thank you for replying! much appreciated.

[Ataya95]

im getting this error as well can you help with this as well? thank you!

---

ValueError Traceback (most recent call last)
in
----> 1 cnnhistory=model.fit(x_traincnn, y_train, batch_size=16, epochs=700, validation_data=(x_testcnn, y_test))

F:\Installed Softwares\Anaconda\lib\site-packages\keras\engine\training.py in fit(self, x, y, batch_size, epochs, verbose, callbacks, validation_split, validation_data, shuffle, class_weight, sample_weight, initial_epoch, steps_per_epoch, validation_steps, **kwargs)
950 sample_weight=sample_weight,
951 class_weight=class_weight,
--> 952 batch_size=batch_size)
953 # Prepare validation data.
954 do_validation = False

F:\Installed Softwares\Anaconda\lib\site-packages\keras\engine\training.py in _standardize_user_data(self, x, y, sample_weight, class_weight, check_array_lengths, batch_size)
787 feed_output_shapes,
788 check_batch_axis=False, # Don't enforce the batch size.
--> 789 exception_prefix='target')
790
791 # Generate sample-wise weight values given the sample_weight and

F:\Installed Softwares\Anaconda\lib\site-packages\keras\engine\training_utils.py in standardize_input_data(data, names, shapes, check_batch_axis, exception_prefix)
136 ': expected ' + names[i] + ' to have shape ' +
137 str(shape) + ' but got array with shape ' +
--> 138 str(data_shape))
139 return data
140

ValueError: Error when checking target: expected activation_20 to have shape (10,) but got array with shape (5,)

[MiteshPuthran]

@Ataya95 , No you don't need to download all the audio files. You just need to load the saved model and then just upload your audio file. It will automatically clip it to 4 seconds and those extracted features will be fed to the model to predict the emotions.

The error you are getting is related to the model building step where changed some parameter related to input size in the activation_20 layer.

[Ataya95]

Thank you so much