update

speech_asr

2023-04-20 8d6244812a0a22d9a88ad897fe6df1b435fe10ab

update

 funasr/build_utils/build_args.py

@@ -74,6 +74,13 @@
            help="The model file of sentencepiece",
        )
        parser.add_argument(
            "--cleaner",
            type=str_or_none,
            choices=[None, "tacotron", "jaconv", "vietnamese"],
            default=None,
            help="Apply text cleaning",
        )
        parser.add_argument(
            "--cmvn_file",
            type=str_or_none,
            default=None,
@@ -135,6 +142,52 @@
            default=0.0,
            help="weights for additional loss terms (not first one)",
        )
    elif args.task_name == "lm":
        from funasr.build_utils.build_lm_model import class_choices_list
        for class_choices in class_choices_list:
            # Append --<name> and --<name>_conf.
            # e.g. --encoder and --encoder_conf
            class_choices.add_arguments(parser)
        parser.add_argument(
            "--token_list",
            type=str_or_none,
            default=None,
            help="A text mapping int-id to token",
        )
        parser.add_argument(
            "--init",
            type=lambda x: str_or_none(x.lower()),
            default=None,
            help="The initialization method",
            choices=[
                "chainer",
                "xavier_uniform",
                "xavier_normal",
                "kaiming_uniform",
                "kaiming_normal",
                None,
            ],
        )
        parser.add_argument(
            "--token_type",
            type=str,
            default="bpe",
            choices=["bpe", "char", "word"],
            help="",
        )
        parser.add_argument(
            "--bpemodel",
            type=str_or_none,
            default=None,
            help="The model file fo sentencepiece",
        )
        parser.add_argument(
            "--cleaner",
            type=str_or_none,
            choices=[None, "tacotron", "jaconv", "vietnamese"],
            default=None,
            help="Apply text cleaning",
        )
    else:
        raise NotImplementedError("Not supported task: {}".format(args.task_name))