def METHOD_NAME(
    data_folder,
    save_json_train,
    save_json_valid,
    save_json_test,
    split_ratio=[80, 10, 10],
):
    """
    Prepares the json files for the Mini Librispeech dataset.
    Downloads the dataset if it is not found in the `data_folder`.
    Arguments
    ---------
    data_folder : str
        Path to the folder where the Mini Librispeech dataset is stored.
    save_json_train : str
        Path where the train data specification file will be saved.
    save_json_valid : str
        Path where the validation data specification file will be saved.
    save_json_test : str
        Path where the test data specification file will be saved.
    split_ratio: list
        List composed of three integers that sets split ratios for train, valid,
        and test sets, respectively. For instance split_ratio=[80, 10, 10] will
        assign 80% of the sentences to training, 10% for validation, and 10%
        for test.
    Example
    -------
    >>> data_folder = '/path/to/mini_librispeech'
    >>> prepare_mini_librispeech(data_folder, 'train.json', 'valid.json', 'test.json')
    """
    # Check if this phase is already done (if so, skip it)
    if skip(save_json_train, save_json_valid, save_json_test):
        logger.info("Preparation completed in previous run, skipping.")
        return
    # If the dataset doesn't exist yet, download it
    train_folder = os.path.join(data_folder, "LibriSpeech", "train-clean-5")
    if not check_folders(train_folder):
        download_mini_librispeech(data_folder)
    # List files and create manifest from list
    logger.info(
        f"Creating {save_json_train}, {save_json_valid}, and {save_json_test}"
    )
    extension = [".flac"]
    wav_list = get_all_files(train_folder, match_and=extension)
    # Random split the signal list into train, valid, and test sets.
    data_split = split_sets(wav_list, split_ratio)
    # Creating json files
    create_json(data_split["train"], save_json_train)
    create_json(data_split["valid"], save_json_valid)
    create_json(data_split["test"], save_json_test)