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update itn_pipeline.md

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chong.zhang 2023-05-05 16:43:06 +08:00
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docs/modelscope_pipeline/itn_pipeline.md
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@ -46,17 +46,18 @@ Full code of demo, please ref to [demo](https://github.com/alibaba-damo-academy/
In this case of `text file` input, `output_dir` must be set to save the output results
## Modify Your Own ITN Model
The rule-based ITN code is open-sourced in [FunTextProcessing](https://github.com/alibaba-damo-academy/FunASR/tree/main/fun_text_processing), users can modify by their own grammar rules for different languages. Let's take Japanese as an example, users can add their own whitelist in fun_text_processing/inverse_text_normalization/ja/data/whitelist.tsv. After modify the rules, the users can export their own ITN models in local directory.
The rule-based ITN code is open-sourced in [FunTextProcessing](https://github.com/alibaba-damo-academy/FunASR/tree/main/fun_text_processing), users can modify by their own grammar rules for different languages. Let's take Japanese as an example, users can add their own whitelist in ```FunASR/fun_text_processing/inverse_text_normalization/ja/data/whitelist.tsv```. After modified the grammar rules, the users can export and evaluate their own ITN models in local directory.
### Export ITN Model
Use the code in FunASR to export ITN model. An example to export ITN model to local folder is shown as below.
Export ITN model via ```FunASR/fun_text_processing/inverse_text_normalization/export_models.py```. An example to export ITN model to local folder is shown as below.
```shell
cd fun_text_processing/inverse_text_normalization/
cd FunASR/fun_text_processing/inverse_text_normalization/
python export_models.py --language ja --export_dir ./itn_models/
```
### Evaluate ITN Model
Users can evaluate their own ITN model in local directory. Here is an example:
Users can evaluate their own ITN model in local directory via ```FunASR/fun_text_processing/inverse_text_normalization/inverse_normalize.py```. Here is an example:
```shell
python fun_text_processing/inverse_text_normalization/inverse_normalize.py --input_file ja_itn_example.txt --cache_dir ./itn_models/ --output_file output.txt --language=ja
cd FunASR/fun_text_processing/inverse_text_normalization/
python inverse_normalize.py --input_file ja_itn_example.txt --cache_dir ./itn_models/ --output_file output.txt --language=ja
```