def METHOD_NAME(state_dict, axes):
    # Remove the seemingly unnecessary axis
    # For ASR task, the pretrained weights originated from fairseq has unrelated dimensions at index 1, 2, 3
    # It's originated from the Dictionary implementation of fairseq, which was intended for NLP tasks,
    # but not used during the ASR training.
    # https://github.com/pytorch/fairseq/blob/c5ff181125c7e6126b49a85e5ebdd5f5b6a07914/fairseq/data/dictionary.py#L21-L37
    # https://github.com/pytorch/fairseq/blob/c5ff181125c7e6126b49a85e5ebdd5f5b6a07914/fairseq/criterions/ctc.py#L126-L129
    #
    # Also, some pretrained weights originated from voxpopuli has an extra dimensions that almost never used and
    # that resembles mistake.
    # The label `1` shows up in the training dataset of German (1 out of 16M),
    # English (1 / 28M), Spanish (1 / 9.4M), Romanian (1 / 4.7M) and Polish (6 / 5.8M)
    for key in ["aux.weight", "aux.bias"]:
        mat = state_dict[key]
        state_dict[key] = torch.stack([mat[i] for i in range(mat.size(0)) if i not in axes])