| | |
| | | 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 |
| | |
| | | paraformer_bert=ParaformerBert, |
| | | bicif_paraformer=BiCifParaformer, |
| | | contextual_paraformer=ContextualParaformer, |
| | | neatcontextual_paraformer=NeatContextualParaformer, |
| | | mfcca=MFCCA, |
| | | timestamp_prediction=TimestampPredictor, |
| | | rnnt=TransducerModel, |
| | |
| | | if args.normalize is not None: |
| | | normalize_class = normalize_choices.get_class(args.normalize) |
| | | if args.model == "mfcca": |
| | | normalize = normalize_class(stats_file=args.cmvn_file,**args.normalize_conf) |
| | | normalize = normalize_class(stats_file=args.cmvn_file, **args.normalize_conf) |
| | | else: |
| | | normalize = normalize_class(**args.normalize_conf) |
| | | else: |