| | |
| | | ```python |
| | | python infer.py |
| | | ``` |
| | | |
| | | ### Inference using local finetuned model |
| | | |
| | | - Modify inference related parameters in `infer_after_finetune.py` |
| | | - <strong>output_dir:</strong> # result dir |
| | | - <strong>data_dir:</strong> # the dataset dir needs to include `test/wav.scp`. If `test/text` is also exists, CER will be computed |
| | | - <strong>decoding_model_name:</strong> # set the checkpoint name for decoding, e.g., `valid.cer_ctc.ave.pb` |
| | | |
| | | - Then you can run the pipeline to finetune with: |
| | | ```python |
| | | python infer_after_finetune.py |
| | | ``` |
| | | |
| | | - Results |
| | | |
| | | The decoding results can be found in `$output_dir/decoding_results/text.cer`, which includes recognition results of each sample and the CER metric of the whole test set. |