update

嘉渊

2023-04-24 6427c834dfd97b1f05c6659cdc7ccf010bf82fe1

 egs_modelscope/asr/uniasr/speech_UniASR_asr_2pass-zh-cn-8k-common-vocab3445-pytorch-online/infer_after_finetune.py

@@ -34,12 +34,12 @@
        batch_size=1
    )
    audio_in = os.path.join(params["data_dir"], "wav.scp")
    inference_pipeline(audio_in=audio_in)
    inference_pipeline(audio_in=audio_in, param_dict={"decoding_model": "normal"})

    # computer CER if GT text is set
    text_in = os.path.join(params["data_dir"], "text")
    if os.path.exists(text_in):
        text_proc_file = os.path.join(decoding_path, "1best_recog/token")
        text_proc_file = os.path.join(decoding_path, "1best_recog/text")
        compute_wer(text_in, text_proc_file, os.path.join(decoding_path, "text.cer"))


@@ -49,5 +49,5 @@
    params["required_files"] = ["am.mvn", "decoding.yaml", "configuration.json"]
    params["output_dir"] = "./checkpoint"
    params["data_dir"] = "./data/test"
    params["decoding_model_name"] = "20epoch.pth"
    params["decoding_model_name"] = "20epoch.pb"
    modelscope_infer_after_finetune(params)