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嘉渊 2023-05-29 10:19:46 +08:00
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docs/academic_recipe/asr_recipe.md
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@ -35,6 +35,9 @@ Also, users can use tensorboard to observe these training information by the fol
```sh ```sh
tensorboard --logdir ${exp_dir}/exp/${model_dir}/tensorboard/train tensorboard --logdir ${exp_dir}/exp/${model_dir}/tensorboard/train
``` ```
Here is an example of loss:
<img src="images/loss.png" width="200"/>
The inference results are saved in `${exp_dir}/exp/${model_dir}/decode_asr_*/$dset`. The main two files are `text.cer` and `text.cer.txt`. `text.cer` saves the comparison between the recognized text and the reference text, like follows: The inference results are saved in `${exp_dir}/exp/${model_dir}/decode_asr_*/$dset`. The main two files are `text.cer` and `text.cer.txt`. `text.cer` saves the comparison between the recognized text and the reference text, like follows:
```text ```text
@ -177,7 +180,7 @@ The configuration of the model is set in the config file `conf/train_*.yaml`. Sp
encoder: conformer encoder: conformer
encoder_conf: encoder_conf:
output_size: 256 # dimension of attention output_size: 256 # dimension of attention
attention_heads: 4 # number of heads in multi-head attention attention_heads: 4 # the number of heads in multi-head attention
linear_units: 2048 # the number of units of position-wise feed forward linear_units: 2048 # the number of units of position-wise feed forward
num_blocks: 12 # the number of encoder blocks num_blocks: 12 # the number of encoder blocks
dropout_rate: 0.1 dropout_rate: 0.1

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