def METHOD_NAME(
    train_val_path: str, train_val_ratio: float = 0.92, random_seed: int = 0
) -> Union[List[str], List[str]]:
    """Splits the folders in 'train_val_path' into the train set and test set,
       and returns the full Train/Validation files.
    Args:
    train_val_path (str): Path to the Folder with the Train/Val data
    train_val_ratio (float): Ratio of the Train/Test file ratio
    random_seed (int): Seed for the file shufling
    Returns:
    speakers_train (list) : Paths of Speaker Folders for Training Data
    speakers_val (list) : Paths of Speaker Folders for Validation Data
    """
    speaker_folders = os.listdir(train_val_path)
    np.random.seed(random_seed)
    np.random.shuffle(speaker_folders)
    num_speakers = len(speaker_folders)
    num_train = int(train_val_ratio * num_speakers)
    speakers_train = speaker_folders[0:num_train]
    speakers_val = speaker_folders[num_train:]
    speakers_train = [
        os.path.join(train_val_path, folder) for folder in speakers_train
    ]
    speakers_val = [os.path.join(train_val_path, folder) for folder in speakers_val]
    return speakers_train, speakers_val