| | |
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| | | |
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| | | Or you can use the finetuned model for inference directly. |
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| | | |
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| | | - Setting parameters in `infer.py` |
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| | | - Setting parameters in `infer.sh` |
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| | | - <strong>model:</strong> # model name on ModelScope |
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| | | - <strong>data_dir:</strong> # the dataset dir needs to include `test/wav.scp`. If `test/text` is also exists, CER will be computed |
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| | | - <strong>output_dir:</strong> # result dir |
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| | | - <strong>ngpu:</strong> # the number of GPUs for decoding |
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| | | - <strong>njob:</strong> # the number of jobs for each GPU |
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| | | - <strong>batch_size:</strong> # batchsize of inference |
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| | | - <strong>gpu_inference:</strong> # whether to perform gpu decoding, set false for cpu decoding |
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| | | - <strong>gpuid_list:</strong> # set gpus, e.g., gpuid_list="0,1" |
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| | | - <strong>njob:</strong> # the number of jobs for CPU decoding, if `gpu_inference`=false, use CPU decoding, please set `njob` |
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| | | |
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| | | - Then you can run the pipeline to infer with: |
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| | | ```python |
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| | | python infer.py |
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| | | sh infer.sh |
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| | | ``` |
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| | | |
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| | | - Results |
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| | | |
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| | | The decoding results can be found in `$output_dir/1best_recog/text.cer`, which includes recognition results of each sample and the CER metric of the whole test set. |
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| | | |
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| | | If you decode the SpeechIO test sets, you can use textnorm with `stage`=3, and `DETAILS.txt`, `RESULTS.txt` record the results and CER after text normalization. |
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| | | |
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| | | ### Inference using local finetuned model |
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| | | |
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| | | - Modify inference related parameters in `infer_after_finetune.py` |
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| | | - <strong>modelscope_model_name: </strong> # model name on ModelScope |
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| | | - <strong>output_dir:</strong> # result dir |
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| | | - <strong>data_dir:</strong> # the dataset dir needs to include `test/wav.scp`. If `test/text` is also exists, CER will be computed |
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| | | - <strong>decoding_model_name:</strong> # set the checkpoint name for decoding, e.g., `valid.cer_ctc.ave.pb` |
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| | | - <strong>batch_size:</strong> # batchsize of inference |
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| | | |
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| | | - Then you can run the pipeline to finetune with: |
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| | | ```python |
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