def STFT_L2_distance()

in evaluate.py [0:0]

• 21 lines of code
• 1 McCabe index (conditional complexity)

def STFT_L2_distance(predicted_binaural, gt_binaural):
    #channel1
    predicted_spect_channel1 = librosa.core.stft(np.asfortranarray(predicted_binaural[0,:]), n_fft=512, hop_length=160, win_length=400, center=True)
    gt_spect_channel1 = librosa.core.stft(np.asfortranarray(gt_binaural[0,:]), n_fft=512, hop_length=160, win_length=400, center=True)
    real = np.expand_dims(np.real(predicted_spect_channel1), axis=0)
    imag = np.expand_dims(np.imag(predicted_spect_channel1), axis=0)
    predicted_realimag_channel1 = np.concatenate((real, imag), axis=0)
    real = np.expand_dims(np.real(gt_spect_channel1), axis=0)
    imag = np.expand_dims(np.imag(gt_spect_channel1), axis=0)
    gt_realimag_channel1 = np.concatenate((real, imag), axis=0)
    channel1_distance = np.mean(np.power((predicted_realimag_channel1 - gt_realimag_channel1), 2))

    #channel2
    predicted_spect_channel2 = librosa.core.stft(np.asfortranarray(predicted_binaural[1,:]), n_fft=512, hop_length=160, win_length=400, center=True)
    gt_spect_channel2 = librosa.core.stft(np.asfortranarray(gt_binaural[1,:]), n_fft=512, hop_length=160, win_length=400, center=True)
    real = np.expand_dims(np.real(predicted_spect_channel2), axis=0)
    imag = np.expand_dims(np.imag(predicted_spect_channel2), axis=0)
    predicted_realimag_channel2 = np.concatenate((real, imag), axis=0)
    real = np.expand_dims(np.real(gt_spect_channel2), axis=0)
    imag = np.expand_dims(np.imag(gt_spect_channel2), axis=0)
    gt_realimag_channel2 = np.concatenate((real, imag), axis=0)
    channel2_distance = np.mean(np.power((predicted_realimag_channel2 - gt_realimag_channel2), 2))

    #sum the distance between two channels
    stft_l2_distance = channel1_distance + channel2_distance
    return float(stft_l2_distance)