def METHOD_NAME():
    # get arguments
    args = get_preprocess_args()
    mel_dim = num_mels * (1 + int(args.delta) + int(args.delta_delta))
    mfcc_dim = num_mfcc * (1 + int(args.delta) + int(args.delta_delta))
    dim = num_freq if args.feature_type == 'linear' else (mfcc_dim if args.feature_type == 'mfcc' else mel_dim)
    print('Delta: ', args.delta, '. Delta Delta: ', args.delta_delta, '. Cmvn: ', args.apply_cmvn)
    # Select data sets
    for idx, s in enumerate(SETS):
        print('\t', idx, ':', s)
    tr_set = input('Please enter the index of splits you wish to use preprocess. (seperate with space): ')
    tr_set = [SETS[int(t)] for t in tr_set.split(' ')]
    # Acoustic Feature Extraction & Make Data Table
    acoustic_preprocess(args, tr_set, dim, args.audio_extention)