def METHOD_NAME(files: str, **kwargs):
    waveforms = []
    srs = []
    max_length = float('-inf')
    for file in files:
        waveform, sr = load_audio(file)
        max_length = max(max_length, len(waveform))
        waveforms.append(waveform)
        srs.append(sr)
    feats = []
    for i in range(len(waveforms)):
        # padding
        if len(waveforms[i]) < max_length:
            pad_width = max_length - len(waveforms[i])
            waveforms[i] = np.pad(waveforms[i], pad_width=(0, pad_width))
        feat = MelSpectrogram(waveforms[i], sr, **kwargs).transpose()
        feats.append(feat)
    return np.stack(feats, axis=0)