update uniasr infer finetune scripts

onlybetheone

2023-03-10 73034847730f7786900f389ec0c8645554fc5eb6

update uniasr infer finetune scripts

 egs_modelscope/asr/uniasr/speech_UniASR_asr_2pass-ja-16k-common-vocab93-tensorflow1-offline/finetune.py

@@ -30,6 +30,6 @@
    params["dataset_type"] = "small"
    params["max_epoch"] = 50
    params["lr"] = 0.00005
    params["model"] = "damo/speech_UniASR_asr_2pass-ja-16k-common-vocab93-tensorflow1-online"
    params["model"] = "damo/speech_UniASR_asr_2pass-ja-16k-common-vocab93-tensorflow1-offline"
    params["model_revision"] = None
    modelscope_finetune(params)

 egs_modelscope/asr/uniasr/speech_UniASR_asr_2pass-ja-16k-common-vocab93-tensorflow1-offline/infer.py

@@ -6,7 +6,7 @@
    output_dir = "./results"
    inference_pipline = pipeline(
        task=Tasks.auto_speech_recognition,
        model="damo/speech_UniASR_asr_2pass-ja-16k-common-vocab93-tensorflow1-online",
        model="damo/speech_UniASR_asr_2pass-ja-16k-common-vocab93-tensorflow1-offline",
        output_dir=output_dir,
    )
    rec_result = inference_pipline(audio_in=audio_in, param_dict={"decoding_model":"offline"})

 egs_modelscope/asr/uniasr/speech_UniASR_asr_2pass-pt-16k-common-vocab1617-tensorflow1-offline/finetune.py

@@ -30,6 +30,6 @@
    params["dataset_type"] = "small"
    params["max_epoch"] = 50
    params["lr"] = 0.00005
    params["model"] = "damo/speech_UniASR_asr_2pass-pt-16k-common-vocab1617-tensorflow1-online"
    params["model"] = "damo/speech_UniASR_asr_2pass-pt-16k-common-vocab1617-tensorflow1-offline"
    params["model_revision"] = None
    modelscope_finetune(params)

 egs_modelscope/asr/uniasr/speech_UniASR_asr_2pass-pt-16k-common-vocab1617-tensorflow1-offline/infer.py

@@ -6,7 +6,7 @@
    output_dir = "./results"
    inference_pipline = pipeline(
        task=Tasks.auto_speech_recognition,
        model="damo/speech_UniASR_asr_2pass-pt-16k-common-vocab1617-tensorflow1-online",
        model="damo/speech_UniASR_asr_2pass-pt-16k-common-vocab1617-tensorflow1-offline",
        output_dir=output_dir,
    )
    rec_result = inference_pipline(audio_in=audio_in, param_dict={"decoding_model":"offline"})