update repo

嘉渊

2023-06-16 66b4f1b8d559d30471dfb6c59167273559c7c85d

 funasr/build_utils/build_asr_model.py

@@ -21,6 +21,7 @@
from funasr.models.decoder.transformer_decoder import ParaformerDecoderSAN
from funasr.models.decoder.transformer_decoder import TransformerDecoder
from funasr.models.e2e_asr import ASRModel
from funasr.models.e2e_asr_contextual_paraformer import NeatContextualParaformer
from funasr.models.e2e_asr_mfcca import MFCCA
from funasr.models.e2e_asr_paraformer import Paraformer, ParaformerOnline, ParaformerBert, BiCifParaformer, \
    ContextualParaformer
@@ -87,6 +88,7 @@
        paraformer_bert=ParaformerBert,
        bicif_paraformer=BiCifParaformer,
        contextual_paraformer=ContextualParaformer,
        neatcontextual_paraformer=NeatContextualParaformer,
        mfcca=MFCCA,
        timestamp_prediction=TimestampPredictor,
        rnnt=TransducerModel,
@@ -239,6 +241,7 @@
        vocab_size = len(token_list)
        logging.info(f"Vocabulary size: {vocab_size}")
    else:
        token_list = None
        vocab_size = None

    # frontend
@@ -265,7 +268,10 @@
    # normalization layer
    if args.normalize is not None:
        normalize_class = normalize_choices.get_class(args.normalize)
        normalize = normalize_class(**args.normalize_conf)
        if args.model == "mfcca":
            normalize = normalize_class(stats_file=args.cmvn_file, **args.normalize_conf)
        else:
            normalize = normalize_class(**args.normalize_conf)
    else:
        normalize = None

@@ -300,7 +306,7 @@
            **args.model_conf,
        )
    elif args.model in ["paraformer", "paraformer_online", "paraformer_bert", "bicif_paraformer",
                        "contextual_paraformer"]:
                        "contextual_paraformer", "neatcontextual_paraformer"]:
        # predictor
        predictor_class = predictor_choices.get_class(args.predictor)
        predictor = predictor_class(**args.predictor_conf)