fix infer_after_finetune.py

jmwang66

2023-02-01 65b35ca42351ee48b6c94530b6414d24cc9745fb

fix infer_after_finetune.py

 egs_modelscope/asr/data2vec/speech_data2vec_pretrain-zh-cn-aishell2-16k-pytorch/infer_after_finetune.py

@@ -37,7 +37,7 @@

    # computer CER if GT text is set
    text_in = os.path.join(params["data_dir"], "text")
    if text_in is not None:
    if os.path.exists(text_in):
        text_proc_file = os.path.join(decoding_path, "1best_recog/token")
        compute_wer(text_in, text_proc_file, os.path.join(decoding_path, "text.cer"))


 egs_modelscope/asr/paraformer/speech_paraformer-large_asr_nat-zh-cn-16k-aishell1-vocab8404-pytorch/infer_after_finetune.py

@@ -38,7 +38,7 @@

    # computer CER if GT text is set
    text_in = os.path.join(params["data_dir"], "text")
    if text_in is not None:
    if os.path.exists(text_in):
        text_proc_file = os.path.join(decoding_path, "1best_recog/token")
        compute_wer(text_in, text_proc_file, os.path.join(decoding_path, "text.cer"))


 egs_modelscope/asr/paraformer/speech_paraformer-large_asr_nat-zh-cn-16k-aishell2-vocab8404-pytorch/infer_after_finetune.py

@@ -38,7 +38,7 @@

    # computer CER if GT text is set
    text_in = os.path.join(params["data_dir"], "text")
    if text_in is not None:
    if os.path.exists(text_in):
        text_proc_file = os.path.join(decoding_path, "1best_recog/token")
        compute_wer(text_in, text_proc_file, os.path.join(decoding_path, "text.cer"))


 egs_modelscope/asr/paraformer/speech_paraformer-large_asr_nat-zh-cn-16k-common-vocab8404-pytorch/infer_after_finetune.py

@@ -38,7 +38,7 @@

    # computer CER if GT text is set
    text_in = os.path.join(params["data_dir"], "text")
    if text_in is not None:
    if os.path.exists(text_in):
        text_proc_file = os.path.join(decoding_path, "1best_recog/token")
        compute_wer(text_in, text_proc_file, os.path.join(decoding_path, "text.cer"))


 egs_modelscope/asr/paraformer/speech_paraformer_asr_nat-zh-cn-8k-common-vocab8358-tensorflow1/infer_after_finetune.py

@@ -38,7 +38,7 @@

    # computer CER if GT text is set
    text_in = os.path.join(params["data_dir"], "text")
    if text_in is not None:
    if os.path.exists(text_in):
        text_proc_file = os.path.join(decoding_path, "1best_recog/token")
        compute_wer(text_in, text_proc_file, os.path.join(decoding_path, "text.cer"))