Valueerror: Could Not Broadcast Input Array From Shape (20,590) Into Shape (20)

I am trying to extract features from .wav files by using MFCC's of the sound files. I am getting an error when I try to convert my list of MFCC's to a numpy array. I am quite sure

Solution 1:

Use the following logic to downsample the arrays to min_shape i.e. reduce larger arrays to min_shape

min_shape = (20, 345)
MFCCs = [arr1, arr2, arr3, ...]    

for idx, arr in enumerate(MFCCs):
    MFCCs[idx] = arr[:, :min_shape[1]]

batch_arr = np.array(MFCCs)

And then you can stack these arrays in a batch array as in the below minimal example:

In [33]: a1 = np.random.randn(2, 3)    
In [34]: a2 = np.random.randn(2, 5)    
In [35]: a3 = np.random.randn(2, 10)

In [36]: MFCCs = [a1, a2, a3]

In [37]: min_shape = (2, 2)

In [38]: for idx, arr in enumerate(MFCCs):
    ...:     MFCCs[idx] = arr[:, :min_shape[1]]
    ...:     

In [42]: batch_arr = np.array(MFCCs)

In [43]: batch_arr.shape
Out[43]: (3, 2, 2)

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Now for the second strategy, to upsample the arrays smaller arrays to max_shape, follow similar logic but fill the missing values with either zeros or nan values as you prefer.

And then again, you can stack the arrays as a batch array of shape (num_arrays, dim1, dim2); So, for your case, the shape should be (num_wav_files, 20, max_column)