def METHOD_NAME(self, audio_values, padding_mask: Optional = None) -> List[np.ndarray]:
    """
    This method strips any padding from the audio values to return a list of numpy audio arrays.
    """
    audio_values = to_numpy(audio_values)
    bsz, channels, seq_len = audio_values.shape
    if padding_mask is None:
        return list(audio_values)
    padding_mask = to_numpy(padding_mask)
    # match the sequence length of the padding mask to the generated audio arrays by padding with the **non-padding**
    # token (so that the generated audio values are **not** treated as padded tokens)
    difference = seq_len - padding_mask.shape[-1]
    padding_value = 1 - self.feature_extractor.padding_value
    padding_mask = np.pad(padding_mask, ((0, 0), (0, difference)), "constant", constant_values=padding_value)
    audio_values = audio_values.tolist()
    for i in range(bsz):
        sliced_audio = np.asarray(audio_values[i])[
            padding_mask[i][None, :] != self.feature_extractor.padding_value
        ]
        audio_values[i] = sliced_audio.reshape(channels, -1)
    return audio_values