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add itn_pipeline.md

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chong.zhang 2023-05-05 16:29:05 +08:00
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docs/modelscope_pipeline/itn_pipeline.md
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@ -30,17 +30,17 @@ rec_result = inference_pipeline(text_in='https://isv-data.oss-cn-hangzhou.aliyun
Full code of demo, please ref to [demo](https://github.com/alibaba-damo-academy/FunASR/tree/main/fun_text_processing/inverse_text_normalization) Full code of demo, please ref to [demo](https://github.com/alibaba-damo-academy/FunASR/tree/main/fun_text_processing/inverse_text_normalization)
#### Modify Your Own ITN Model ### 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. 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. After modify the rules, the users can export their own ITN models in local directory.
##### Export ITN Model ### 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. Use the code in FunASR to export ITN model. An example to export ITN model to local folder is shown as below.
```shell ```shell
cd fun_text_processing/inverse_text_normalization/ cd fun_text_processing/inverse_text_normalization/
python export_models.py --language ja --export_dir ./itn_models/ python export_models.py --language ja --export_dir ./itn_models/
``` ```
##### Evaluate ITN Model ### 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. Here is an example:
```shell ```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 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
@ -58,13 +58,4 @@ python fun_text_processing/inverse_text_normalization/inverse_normalize.py --inp
- text bytes, `e.g.`: "一九九九年に誕生した同商品にちなみ、約三十年前、二十四歳の頃の幸四郎の写真を公開。" - text bytes, `e.g.`: "一九九九年に誕生した同商品にちなみ、約三十年前、二十四歳の頃の幸四郎の写真を公開。"
- text file, `e.g.`: https://isv-data.oss-cn-hangzhou.aliyuncs.com/ics/MaaS/ASR/test_text/ja_itn_example.txt - text file, `e.g.`: https://isv-data.oss-cn-hangzhou.aliyuncs.com/ics/MaaS/ASR/test_text/ja_itn_example.txt
In this case of `text file` input, `output_dir` must be set to save the output results In this case of `text file` input, `output_dir` must be set to save the output results
## Finetune with pipeline
### Quick start
### Finetune with your data
## Inference with your finetuned model