recipes/conv_glu/wsj/prepare.py [43:91]:
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    return spelling


if __name__ == "__main__":
    parser = argparse.ArgumentParser(description="Librispeech Dataset creation.")
    parser.add_argument("--wsj0", help="top level directory containing all WSJ0 discs")
    parser.add_argument("--wsj1", help="top level directory containing all WSJ1 discs")
    parser.add_argument(
        "--data_dst", help="data destination directory", default="./wsj"
    )
    parser.add_argument(
        "--model_dst",
        help="model auxilary files destination directory",
        default="./conv_glu_librispeech_char",
    )
    parser.add_argument(
        "--wsj1_type",
        help="if you are using larger corpus LDC94S13A, set parameter to `LDC94S13A`",
        default="LDC94S13B",
    )
    parser.add_argument(
        "--sph2pipe",
        help="path to sph2pipe executable",
        default="./sph2pipe_v2.5/sph2pipe",
    )
    parser.add_argument("--kenlm", help="location to installed kenlm directory")
    parser.add_argument(
        "-p", "--process", help="# of process for Multiprocessing", default=8, type=int
    )
    args = parser.parse_args()
    os.system(
        "python3 {}/../../../data/wsj/prepare.py "
        "--wsj0 {} --wsj1 {} --sph2pipe {} --wsj1_type {} --dst {} -p {}".format(
            os.path.dirname(os.path.abspath(__file__)),
            args.wsj0,
            args.wsj1,
            args.sph2pipe,
            args.wsj1_type,
            args.data_dst,
            args.process,
        )
    )

    lists_path = os.path.join(args.data_dst, "lists")
    am_path = os.path.join(args.model_dst, "am")
    lm_data_path = os.path.join(args.data_dst, "text/lm.txt")
    decoder_path = os.path.join(args.model_dst, "decoder")
    os.makedirs(am_path, exist_ok=True)
    os.makedirs(decoder_path, exist_ok=True)
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recipes/lexicon_free/wsj/prepare.py [105:152]:
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    return spelling


if __name__ == "__main__":
    parser = argparse.ArgumentParser(description="Librispeech Dataset creation.")
    parser.add_argument("--wsj0", help="top level directory containing all WSJ0 discs")
    parser.add_argument("--wsj1", help="top level directory containing all WSJ1 discs")
    parser.add_argument(
        "--data_dst", help="data destination directory", default="./wsj"
    )
    parser.add_argument(
        "--model_dst",
        help="model auxilary files destination directory",
        default="./conv_glu_librispeech_char",
    )
    parser.add_argument(
        "--wsj1_type",
        help="if you are using larger corpus LDC94S13A, set parameter to `LDC94S13A`",
        default="LDC94S13B",
    )
    parser.add_argument(
        "--sph2pipe",
        help="path to sph2pipe executable",
        default="./sph2pipe_v2.5/sph2pipe",
    )
    parser.add_argument("--kenlm", help="location to installed kenlm directory")
    parser.add_argument(
        "-p", "--process", help="# of process for Multiprocessing", default=8, type=int
    )
    args = parser.parse_args()
    os.system(
        "python3 {}/../../../data/wsj/prepare.py "
        "--wsj0 {} --wsj1 {} --sph2pipe {} --wsj1_type {} --dst {} -p {}".format(
            os.path.dirname(os.path.abspath(__file__)),
            args.wsj0,
            args.wsj1,
            args.sph2pipe,
            args.wsj1_type,
            args.data_dst,
            args.process,
        )
    )
    lists_path = os.path.join(args.data_dst, "lists")
    am_path = os.path.join(args.model_dst, "am")
    lm_data_path = os.path.join(args.data_dst, "text/lm.txt")
    decoder_path = os.path.join(args.model_dst, "decoder")
    os.makedirs(am_path, exist_ok=True)
    os.makedirs(decoder_path, exist_ok=True)
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