egs_modelscope/asr/uniasr/speech_UniASR_asr_2pass-zh-cn-8k-common-vocab3445-pytorch-offline/infer.py
@@ -25,7 +25,6 @@ audio_in = os.path.join(split_dir, "wav.{}.scp".format(idx)) inference_pipline(audio_in=audio_in) def modelscope_infer(params): # prepare for multi-GPU decoding ngpu = params["ngpu"] @@ -75,7 +74,7 @@ # If text exists, compute CER text_in = os.path.join(params["data_dir"], "text") if os.path.exists(text_in): text_proc_file = os.path.join(best_recog_path, "token") text_proc_file = os.path.join(best_recog_path, "text") compute_wer(text_in, text_proc_file, os.path.join(best_recog_path, "text.cer"))
