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| | | from funasr.models.joint_net.joint_network import JointNetwork |
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| | | from funasr.models.e2e_asr import ESPnetASRModel |
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| | | from funasr.models.e2e_asr_paraformer import Paraformer, ParaformerOnline, ParaformerBert, BiCifParaformer, ContextualParaformer |
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| | | from funasr.models.e2e_asr_contextual_paraformer import AdvancedContextualParaformer |
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| | | from funasr.models.e2e_asr_contextual_paraformer import NeatContextualParaformer |
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| | | from funasr.models.e2e_tp import TimestampPredictor |
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| | | from funasr.models.e2e_asr_mfcca import MFCCA |
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| | | from funasr.models.e2e_uni_asr import UniASR |
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| | |
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| | | paraformer_bert=ParaformerBert, |
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| | | bicif_paraformer=BiCifParaformer, |
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| | | contextual_paraformer=ContextualParaformer, |
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| | | acontextual_paraformer=AdvancedContextualParaformer, |
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| | | neatcontextual_paraformer=NeatContextualParaformer, |
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| | | mfcca=MFCCA, |
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| | | timestamp_prediction=TimestampPredictor, |
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| | | ), |
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| | |
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| | | normalize = None |
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| | | |
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| | | # 4. Encoder |
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| | | |
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| | | if getattr(args, "encoder", None) is not None: |
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| | | encoder_class = encoder_choices.get_class(args.encoder) |
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| | | encoder = encoder_class(input_size, **args.encoder_conf) |
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| | |
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| | | |
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| | | # 7. Build model |
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| | | |
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| | | if encoder.unified_model_training: |
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| | | if hasattr(encoder, 'unified_model_training') and encoder.unified_model_training: |
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| | | model = UnifiedTransducerModel( |
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| | | vocab_size=vocab_size, |
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| | | token_list=token_list, |
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