update

examples/wenet/toolbox_infer.py

@@ -57,13 +57,6 @@ def main():
     nn_model_file = local_model_dir / m_dict["nn_model_file"]
     tokens_file = local_model_dir / m_dict["tokens_file"]
 
-    # recognizer = models.load_sherpa_offline_recognizer(
-    #     nn_model_file=nn_model_file.as_posix(),
-    #     tokens_file=tokens_file.as_posix(),
-    #     decoding_method="greedy_search",
-    #     num_active_paths=2,
-    # )
-
     recognizer = models.load_recognizer(
         repo_id=m_dict["repo_id"],
         nn_model_file=nn_model_file.as_posix(),
@@ -75,21 +68,6 @@ def main():
         num_active_paths=2,
     )
 
-    # feat_config = sherpa.FeatureConfig(normalize_samples=False)
-    # feat_config.fbank_opts.frame_opts.samp_freq = args.sample_rate
-    # feat_config.fbank_opts.mel_opts.num_bins = 80
-    # feat_config.fbank_opts.frame_opts.dither = 0
-    #
-    # config = sherpa.OfflineRecognizerConfig(
-    #     nn_model=nn_model_file.as_posix(),
-    #     tokens=tokens_file.as_posix(),
-    #     use_gpu=False,
-    #     feat_config=feat_config,
-    #     decoding_method="greedy_search",
-    #     num_active_paths=2,
-    # )
-    # recognizer = sherpa.OfflineRecognizer(config)
-
     text = decode.decode_by_recognizer(recognizer=recognizer,
                                        filename=out_filename.as_posix(),
                                        )