def METHOD_NAME():
    parser = get_parser()
    args = parser.parse_args()
    wav_scp_file = os.path.join(args.wav_path, "wav.{}.scp".format(args.idx))
    cmvn_file = os.path.join(args.wav_path, "cmvn.{}.json".format(args.idx))
    mean_stats = np.zeros(args.dim)
    var_stats = np.zeros(args.dim)
    total_frames = 0
    # with ReadHelper('ark:{}'.format(ark_file)) as ark_reader:
    #     for key, mat in ark_reader:
    #         mean_stats += np.sum(mat, axis=0)
    #         var_stats += np.sum(np.square(mat), axis=0)
    #         total_frames += mat.shape[0]
    with open(args.config_file) as f:
        configs = yaml.safe_load(f)
        frontend_configs = configs.get("frontend_conf", {})
        num_mel_bins = frontend_configs.get("n_mels", 80)
        frame_length = frontend_configs.get("frame_length", 25)
        frame_shift = frontend_configs.get("frame_shift", 10)
        window_type = frontend_configs.get("window", "hamming")
        resample_rate = frontend_configs.get("fs", 16000)
        n_fft = frontend_configs.get("n_fft", "400")
        use_channel = frontend_configs.get("use_channel", None)
        assert num_mel_bins == args.dim
    frontend = DefaultFrontend(
        fs=resample_rate,
        n_fft=n_fft,
        win_length=frame_length * 16,
        hop_length=frame_shift * 16,
        window=window_type,
        n_mels=num_mel_bins,
        use_channel=use_channel,
    )
    with open(wav_scp_file) as f:
        lines = f.readlines()
        for line in lines:
            _, wav_file = line.strip().split()
            wavform, _ = torchaudio.load(wav_file)
            fbank, _ = frontend(wavform.transpose(0, 1).unsqueeze(0), torch.tensor([wavform.shape[1]]))
            fbank = fbank.squeeze(0).numpy()
            mean_stats += np.sum(fbank, axis=0)
            var_stats += np.sum(np.square(fbank), axis=0)
            total_frames += fbank.shape[0]
    cmvn_info = {
        'mean_stats': list(mean_stats.tolist()),
        'var_stats': list(var_stats.tolist()),
        'total_frames': total_frames
    }
    with open(cmvn_file, 'w') as fout:
        fout.write(json.dumps(cmvn_info))