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| | | # You can modify the configuration according to your own requirements. |
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| | | |
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| | | # to print the register_table: |
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| | | # from funasr.utils.register import registry_tables |
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| | | # registry_tables.print() |
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| | | # from funasr.register import tables |
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| | | # tables.print() |
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| | | |
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| | | # network architecture |
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| | | #model: funasr.models.paraformer.model:Paraformer |
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| | | model: Transformer |
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| | | model: Conformer |
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| | | model_conf: |
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| | | ctc_weight: 0.3 |
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| | | lsm_weight: 0.1 # label smoothing option |
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| | |
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| | | # encoder |
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| | | encoder: ConformerEncoder |
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| | | encoder_conf: |
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| | | output_size: 256 # dimension of attention |
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| | | output_size: 256 |
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| | | attention_heads: 4 |
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| | | linear_units: 2048 # the number of units of position-wise feed forward |
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| | | num_blocks: 12 # the number of encoder blocks |
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| | | linear_units: 2048 |
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| | | num_blocks: 12 |
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| | | dropout_rate: 0.1 |
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| | | positional_dropout_rate: 0.1 |
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| | | attention_dropout_rate: 0.0 |
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| | | input_layer: conv2d # encoder architecture type |
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| | | input_layer: conv2d |
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| | | normalize_before: true |
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| | | pos_enc_layer_type: rel_pos |
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| | | selfattention_layer_type: rel_selfattn |
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| | |
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| | | n_mels: 80 |
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| | | frame_length: 25 |
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| | | frame_shift: 10 |
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| | | dither: 0.0 |
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| | | lfr_m: 1 |
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| | | lfr_n: 1 |
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| | | |
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| | |
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| | | dataset: AudioDataset |
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| | | dataset_conf: |
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| | | index_ds: IndexDSJsonl |
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| | | batch_sampler: DynamicBatchLocalShuffleSampler |
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| | | batch_sampler: BatchSampler |
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| | | batch_type: example # example or length |
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| | | batch_size: 1 # if batch_type is example, batch_size is the numbers of samples; if length, batch_size is source_token_len+target_token_len; |
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| | | max_token_length: 2048 # filter samples if source_token_len+target_token_len > max_token_length, |
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