docs

egs_modelscope/asr/conformer/speech_conformer_asr_nat-zh-cn-16k-aishell1-vocab4234-pytorch/demo.py

@@ -4,11 +4,11 @@ from modelscope.utils.constant import Tasks
 if __name__ == '__main__':
     audio_in = 'https://isv-data.oss-cn-hangzhou.aliyuncs.com/ics/MaaS/ASR/test_audio/asr_example_zh.wav'
     output_dir = None
-    inference_pipline = pipeline(
+    inference_pipeline = pipeline(
         task=Tasks.auto_speech_recognition,
         model="damo/speech_conformer_asr_nat-zh-cn-16k-aishell1-vocab4234-pytorch",
         output_dir=output_dir,
     )
-    rec_result = inference_pipline(audio_in=audio_in)
+    rec_result = inference_pipeline(audio_in=audio_in)
     print(rec_result)
 

egs_modelscope/asr/conformer/speech_conformer_asr_nat-zh-cn-16k-aishell2-vocab5212-pytorch/demo.py

@@ -4,10 +4,10 @@ from modelscope.utils.constant import Tasks
 if __name__ == "__main__":
     audio_in = "https://modelscope.oss-cn-beijing.aliyuncs.com/test/audios/asr_example.wav"
     output_dir = "./results"
-    inference_pipline = pipeline(
+    inference_pipeline = pipeline(
         task=Tasks.auto_speech_recognition,
         model="damo/speech_conformer_asr_nat-zh-cn-16k-aishell2-vocab5212-pytorch",
         output_dir=output_dir,
     )
-    rec_result = inference_pipline(audio_in=audio_in)
+    rec_result = inference_pipeline(audio_in=audio_in)
     print(rec_result)

egs_modelscope/asr/data2vec/speech_data2vec_pretrain-paraformer-zh-cn-aishell2-16k/infer.py

@@ -16,13 +16,13 @@ def modelscope_infer_core(output_dir, split_dir, njob, idx):
         os.environ['CUDA_VISIBLE_DEVICES'] = str(gpu_list[gpu_id])
     else:
         os.environ['CUDA_VISIBLE_DEVICES'] = str(gpu_id)
-    inference_pipline = pipeline(
+    inference_pipeline = pipeline(
         task=Tasks.auto_speech_recognition,
         model="damo/speech_data2vec_pretrain-paraformer-zh-cn-aishell2-16k",
         output_dir=output_dir_job,
     )
     audio_in = os.path.join(split_dir, "wav.{}.scp".format(idx))
-    inference_pipline(audio_in=audio_in)
+    inference_pipeline(audio_in=audio_in)
 
 
 def modelscope_infer(params):

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

@@ -16,13 +16,13 @@ def modelscope_infer_core(output_dir, split_dir, njob, idx):
         os.environ['CUDA_VISIBLE_DEVICES'] = str(gpu_list[gpu_id])
     else:
         os.environ['CUDA_VISIBLE_DEVICES'] = str(gpu_id)
-    inference_pipline = pipeline(
+    inference_pipeline = pipeline(
         task=Tasks.auto_speech_recognition,
         model="damo/speech_data2vec_pretrain-zh-cn-aishell2-16k-pytorch",
         output_dir=output_dir_job,
     )
     audio_in = os.path.join(split_dir, "wav.{}.scp".format(idx))
-    inference_pipline(audio_in=audio_in)
+    inference_pipeline(audio_in=audio_in)
 
 
 def modelscope_infer(params):

egs_modelscope/asr/paraformer/speech_paraformer-tiny-commandword_asr_nat-zh-cn-16k-vocab544-pytorch/infer.py

@@ -16,14 +16,14 @@ def modelscope_infer_core(output_dir, split_dir, njob, idx):
         os.environ['CUDA_VISIBLE_DEVICES'] = str(gpu_list[gpu_id])
     else:
         os.environ['CUDA_VISIBLE_DEVICES'] = str(gpu_id)
-    inference_pipline = pipeline(
+    inference_pipeline = pipeline(
         task=Tasks.auto_speech_recognition,
         model="damo/speech_paraformer-tiny-commandword_asr_nat-zh-cn-16k-vocab544-pytorch",
         output_dir=output_dir_job,
         batch_size=64
     )
     audio_in = os.path.join(split_dir, "wav.{}.scp".format(idx))
-    inference_pipline(audio_in=audio_in)
+    inference_pipeline(audio_in=audio_in)
 
 
 def modelscope_infer(params):

egs_modelscope/asr/paraformer/speech_paraformer_asr_nat-zh-cn-16k-aishell1-vocab4234-pytorch/demo.py

@@ -4,12 +4,12 @@ from modelscope.utils.constant import Tasks
 if __name__ == '__main__':
     audio_in = 'https://isv-data.oss-cn-hangzhou.aliyuncs.com/ics/MaaS/ASR/test_audio/asr_example_zh.wav'
     output_dir = None
-    inference_pipline = pipeline(
+    inference_pipeline = pipeline(
         task=Tasks.auto_speech_recognition,
         model="damo/speech_paraformer_asr_nat-zh-cn-16k-aishell1-vocab4234-pytorch",
         output_dir=output_dir,
         batch_size=1,
     )
-    rec_result = inference_pipline(audio_in=audio_in)
+    rec_result = inference_pipeline(audio_in=audio_in)
     print(rec_result)
 

egs_modelscope/asr/paraformer/speech_paraformer_asr_nat-zh-cn-16k-aishell2-vocab5212-pytorch/demo.py

@@ -4,10 +4,10 @@ from modelscope.utils.constant import Tasks
 if __name__ == "__main__":
     audio_in = "https://modelscope.oss-cn-beijing.aliyuncs.com/test/audios/asr_example.wav"
     output_dir = "./results"
-    inference_pipline = pipeline(
+    inference_pipeline = pipeline(
         task=Tasks.auto_speech_recognition,
         model="damo/speech_paraformer_asr_nat-zh-cn-16k-aishell2-vocab5212-pytorch",
         output_dir=output_dir,
     )
-    rec_result = inference_pipline(audio_in=audio_in)
+    rec_result = inference_pipeline(audio_in=audio_in)
     print(rec_result)

egs_modelscope/asr/paraformerbert/speech_paraformerbert_asr_nat-zh-cn-16k-aishell1-vocab4234-pytorch/infer.py

@@ -4,11 +4,11 @@ from modelscope.utils.constant import Tasks
 if __name__ == '__main__':
     audio_in = 'https://isv-data.oss-cn-hangzhou.aliyuncs.com/ics/MaaS/ASR/test_audio/asr_example_zh.wav'
     output_dir = None
-    inference_pipline = pipeline(
+    inference_pipeline = pipeline(
         task=Tasks.auto_speech_recognition,
         model="damo/speech_paraformerbert_asr_nat-zh-cn-16k-aishell1-vocab4234-pytorch",
         output_dir=output_dir,
     )
-    rec_result = inference_pipline(audio_in=audio_in)
+    rec_result = inference_pipeline(audio_in=audio_in)
     print(rec_result)
 

egs_modelscope/asr/paraformerbert/speech_paraformerbert_asr_nat-zh-cn-16k-aishell2-vocab5212-pytorch/infer.py

@@ -4,10 +4,10 @@ from modelscope.utils.constant import Tasks
 if __name__ == "__main__":
     audio_in = "https://modelscope.oss-cn-beijing.aliyuncs.com/test/audios/asr_example.wav"
     output_dir = "./results"
-    inference_pipline = pipeline(
+    inference_pipeline = pipeline(
         task=Tasks.auto_speech_recognition,
         model="damo/speech_paraformerbert_asr_nat-zh-cn-16k-aishell2-vocab5212-pytorch",
         output_dir=output_dir,
     )
-    rec_result = inference_pipline(audio_in=audio_in)
+    rec_result = inference_pipeline(audio_in=audio_in)
     print(rec_result)

egs_modelscope/asr/uniasr/speech_UniASR_asr_2pass-cantonese-CHS-16k-common-vocab1468-tensorflow1-offline/infer.py

@@ -4,10 +4,10 @@ from modelscope.utils.constant import Tasks
 if __name__ == "__main__":
     audio_in = "https://isv-data.oss-cn-hangzhou.aliyuncs.com/ics/MaaS/ASR/test_audio/asr_example_cantonese-CHS.wav"
     output_dir = "./results"
-    inference_pipline = pipeline(
+    inference_pipeline = pipeline(
         task=Tasks.auto_speech_recognition,
         model="damo/speech_UniASR_asr_2pass-cantonese-CHS-16k-common-vocab1468-tensorflow1-online",
         output_dir=output_dir,
     )
-    rec_result = inference_pipline(audio_in=audio_in, param_dict={"decoding_model":"offline"})
+    rec_result = inference_pipeline(audio_in=audio_in, param_dict={"decoding_model":"offline"})
     print(rec_result)

egs_modelscope/asr/uniasr/speech_UniASR_asr_2pass-cantonese-CHS-16k-common-vocab1468-tensorflow1-online/infer.py

@@ -4,10 +4,10 @@ from modelscope.utils.constant import Tasks
 if __name__ == "__main__":
     audio_in = "https://isv-data.oss-cn-hangzhou.aliyuncs.com/ics/MaaS/ASR/test_audio/asr_example_cantonese-CHS.wav"
     output_dir = "./results"
-    inference_pipline = pipeline(
+    inference_pipeline = pipeline(
         task=Tasks.auto_speech_recognition,
         model="damo/speech_UniASR_asr_2pass-cantonese-CHS-16k-common-vocab1468-tensorflow1-online",
         output_dir=output_dir,
     )
-    rec_result = inference_pipline(audio_in=audio_in, param_dict={"decoding_model":"normal"})
+    rec_result = inference_pipeline(audio_in=audio_in, param_dict={"decoding_model":"normal"})
     print(rec_result)

egs_modelscope/asr/uniasr/speech_UniASR_asr_2pass-cn-dialect-16k-vocab8358-tensorflow1-offline/infer.py

@@ -4,11 +4,11 @@ from modelscope.utils.constant import Tasks
 if __name__ == '__main__':
     audio_in = 'https://isv-data.oss-cn-hangzhou.aliyuncs.com/ics/MaaS/ASR/test_audio/asr_example_zh.wav'
     output_dir = None
-    inference_pipline = pipeline(
+    inference_pipeline = pipeline(
         task=Tasks.auto_speech_recognition,
         model="damo/speech_UniASR_asr_2pass-cn-dialect-16k-vocab8358-tensorflow1-offline",
         output_dir=output_dir,
     )
-    rec_result = inference_pipline(audio_in=audio_in)
+    rec_result = inference_pipeline(audio_in=audio_in)
     print(rec_result)
 

egs_modelscope/asr/uniasr/speech_UniASR_asr_2pass-cn-dialect-16k-vocab8358-tensorflow1-online/infer.py

@@ -4,11 +4,11 @@ from modelscope.utils.constant import Tasks
 if __name__ == '__main__':
     audio_in = 'https://isv-data.oss-cn-hangzhou.aliyuncs.com/ics/MaaS/ASR/test_audio/asr_example_zh.wav'
     output_dir = None
-    inference_pipline = pipeline(
+    inference_pipeline = pipeline(
         task=Tasks.auto_speech_recognition,
         model="damo/speech_UniASR_asr_2pass-cn-dialect-16k-vocab8358-tensorflow1-online",
         output_dir=output_dir,
     )
-    rec_result = inference_pipline(audio_in=audio_in)
+    rec_result = inference_pipeline(audio_in=audio_in)
     print(rec_result)
 

egs_modelscope/asr/uniasr/speech_UniASR_asr_2pass-de-16k-common-vocab3690-tensorflow1-offline/infer.py

@@ -4,10 +4,10 @@ from modelscope.utils.constant import Tasks
 if __name__ == "__main__":
     audio_in = "https://isv-data.oss-cn-hangzhou.aliyuncs.com/ics/MaaS/ASR/test_audio/asr_example_de.wav"
     output_dir = "./results"
-    inference_pipline = pipeline(
+    inference_pipeline = pipeline(
         task=Tasks.auto_speech_recognition,
         model="damo/speech_UniASR_asr_2pass-de-16k-common-vocab3690-tensorflow1-offline",
         output_dir=output_dir,
     )
-    rec_result = inference_pipline(audio_in=audio_in, param_dict={"decoding_model":"offline"})
+    rec_result = inference_pipeline(audio_in=audio_in, param_dict={"decoding_model":"offline"})
     print(rec_result)

egs_modelscope/asr/uniasr/speech_UniASR_asr_2pass-de-16k-common-vocab3690-tensorflow1-online/infer.py

@@ -4,10 +4,10 @@ from modelscope.utils.constant import Tasks
 if __name__ == "__main__":
     audio_in = "https://isv-data.oss-cn-hangzhou.aliyuncs.com/ics/MaaS/ASR/test_audio/asr_example_de.wav"
     output_dir = "./results"
-    inference_pipline = pipeline(
+    inference_pipeline = pipeline(
         task=Tasks.auto_speech_recognition,
         model="damo/speech_UniASR_asr_2pass-de-16k-common-vocab3690-tensorflow1-online",
         output_dir=output_dir,
     )
-    rec_result = inference_pipline(audio_in=audio_in, param_dict={"decoding_model":"normal"})
+    rec_result = inference_pipeline(audio_in=audio_in, param_dict={"decoding_model":"normal"})
     print(rec_result)

egs_modelscope/asr/uniasr/speech_UniASR_asr_2pass-en-16k-common-vocab1080-tensorflow1-offline/infer.py

@@ -4,10 +4,10 @@ from modelscope.utils.constant import Tasks
 if __name__ == "__main__":
     audio_in = "https://isv-data.oss-cn-hangzhou.aliyuncs.com/ics/MaaS/ASR/test_audio/asr_example_en.wav"
     output_dir = "./results"
-    inference_pipline = pipeline(
+    inference_pipeline = pipeline(
         task=Tasks.auto_speech_recognition,
         model="damo/speech_UniASR_asr_2pass-en-16k-common-vocab1080-tensorflow1-offline",
         output_dir=output_dir,
     )
-    rec_result = inference_pipline(audio_in=audio_in, param_dict={"decoding_model":"offline"})
+    rec_result = inference_pipeline(audio_in=audio_in, param_dict={"decoding_model":"offline"})
     print(rec_result)

egs_modelscope/asr/uniasr/speech_UniASR_asr_2pass-en-16k-common-vocab1080-tensorflow1-online/infer.py

@@ -4,10 +4,10 @@ from modelscope.utils.constant import Tasks
 if __name__ == "__main__":
     audio_in = "https://isv-data.oss-cn-hangzhou.aliyuncs.com/ics/MaaS/ASR/test_audio/asr_example_en.wav"
     output_dir = "./results"
-    inference_pipline = pipeline(
+    inference_pipeline = pipeline(
         task=Tasks.auto_speech_recognition,
         model="damo/speech_UniASR_asr_2pass-en-16k-common-vocab1080-tensorflow1-online",
         output_dir=output_dir,
     )
-    rec_result = inference_pipline(audio_in=audio_in, param_dict={"decoding_model":"normal"})
+    rec_result = inference_pipeline(audio_in=audio_in, param_dict={"decoding_model":"normal"})
     print(rec_result)

egs_modelscope/asr/uniasr/speech_UniASR_asr_2pass-es-16k-common-vocab3445-tensorflow1-offline/infer.py

@@ -4,10 +4,10 @@ from modelscope.utils.constant import Tasks
 if __name__ == "__main__":
     audio_in = "https://isv-data.oss-cn-hangzhou.aliyuncs.com/ics/MaaS/ASR/test_audio/asr_example_es.wav"
     output_dir = "./results"
-    inference_pipline = pipeline(
+    inference_pipeline = pipeline(
         task=Tasks.auto_speech_recognition,
         model="damo/speech_UniASR_asr_2pass-es-16k-common-vocab3445-tensorflow1-offline",
         output_dir=output_dir,
     )
-    rec_result = inference_pipline(audio_in=audio_in, param_dict={"decoding_model":"offline"})
+    rec_result = inference_pipeline(audio_in=audio_in, param_dict={"decoding_model":"offline"})
     print(rec_result)

egs_modelscope/asr/uniasr/speech_UniASR_asr_2pass-es-16k-common-vocab3445-tensorflow1-online/infer.py

@@ -4,10 +4,10 @@ from modelscope.utils.constant import Tasks
 if __name__ == "__main__":
     audio_in = "https://isv-data.oss-cn-hangzhou.aliyuncs.com/ics/MaaS/ASR/test_audio/asr_example_es.wav"
     output_dir = "./results"
-    inference_pipline = pipeline(
+    inference_pipeline = pipeline(
         task=Tasks.auto_speech_recognition,
         model="damo/speech_UniASR_asr_2pass-es-16k-common-vocab3445-tensorflow1-online",
         output_dir=output_dir,
     )
-    rec_result = inference_pipline(audio_in=audio_in, param_dict={"decoding_model":"normal"})
+    rec_result = inference_pipeline(audio_in=audio_in, param_dict={"decoding_model":"normal"})
     print(rec_result)

egs_modelscope/asr/uniasr/speech_UniASR_asr_2pass-fa-16k-common-vocab1257-pytorch-offline/infer.py

@@ -16,14 +16,14 @@ def modelscope_infer_core(output_dir, split_dir, njob, idx):
         os.environ['CUDA_VISIBLE_DEVICES'] = str(gpu_list[gpu_id])
     else:
         os.environ['CUDA_VISIBLE_DEVICES'] = str(gpu_id)
-    inference_pipline = pipeline(
+    inference_pipeline = pipeline(
         task=Tasks.auto_speech_recognition,
         model="damo/speech_UniASR_asr_2pass-fa-16k-common-vocab1257-pytorch-offline",
         output_dir=output_dir_job,
         batch_size=1
     )
     audio_in = os.path.join(split_dir, "wav.{}.scp".format(idx))
-    inference_pipline(audio_in=audio_in, param_dict={"decoding_model":"offline"})
+    inference_pipeline(audio_in=audio_in, param_dict={"decoding_model":"offline"})
 
 
 def modelscope_infer(params):

egs_modelscope/asr/uniasr/speech_UniASR_asr_2pass-fa-16k-common-vocab1257-pytorch-online/infer.py

@@ -16,14 +16,14 @@ def modelscope_infer_core(output_dir, split_dir, njob, idx):
         os.environ['CUDA_VISIBLE_DEVICES'] = str(gpu_list[gpu_id])
     else:
         os.environ['CUDA_VISIBLE_DEVICES'] = str(gpu_id)
-    inference_pipline = pipeline(
+    inference_pipeline = pipeline(
         task=Tasks.auto_speech_recognition,
         model="damo/speech_UniASR_asr_2pass-fa-16k-common-vocab1257-pytorch-online",
         output_dir=output_dir_job,
         batch_size=1
     )
     audio_in = os.path.join(split_dir, "wav.{}.scp".format(idx))
-    inference_pipline(audio_in=audio_in, param_dict={"decoding_model":"normal"})
+    inference_pipeline(audio_in=audio_in, param_dict={"decoding_model":"normal"})
 
 
 def modelscope_infer(params):

egs_modelscope/asr/uniasr/speech_UniASR_asr_2pass-fr-16k-common-vocab3472-tensorflow1-offline/infer.py

@@ -4,10 +4,10 @@ from modelscope.utils.constant import Tasks
 if __name__ == "__main__":
     audio_in = "https://isv-data.oss-cn-hangzhou.aliyuncs.com/ics/MaaS/ASR/test_audio/asr_example_fr.wav"
     output_dir = "./results"
-    inference_pipline = pipeline(
+    inference_pipeline = pipeline(
         task=Tasks.auto_speech_recognition,
         model="damo/speech_UniASR_asr_2pass-fr-16k-common-vocab3472-tensorflow1-offline",
         output_dir=output_dir,
     )
-    rec_result = inference_pipline(audio_in=audio_in, param_dict={"decoding_model":"offline"})
+    rec_result = inference_pipeline(audio_in=audio_in, param_dict={"decoding_model":"offline"})
     print(rec_result)

egs_modelscope/asr/uniasr/speech_UniASR_asr_2pass-fr-16k-common-vocab3472-tensorflow1-online/infer.py

@@ -4,10 +4,10 @@ from modelscope.utils.constant import Tasks
 if __name__ == "__main__":
     audio_in = "https://isv-data.oss-cn-hangzhou.aliyuncs.com/ics/MaaS/ASR/test_audio/asr_example_fr.wav"
     output_dir = "./results"
-    inference_pipline = pipeline(
+    inference_pipeline = pipeline(
         task=Tasks.auto_speech_recognition,
         model="damo/speech_UniASR_asr_2pass-fr-16k-common-vocab3472-tensorflow1-online",
         output_dir=output_dir,
     )
-    rec_result = inference_pipline(audio_in=audio_in, param_dict={"decoding_model":"normal"})
+    rec_result = inference_pipeline(audio_in=audio_in, param_dict={"decoding_model":"normal"})
     print(rec_result)

egs_modelscope/asr/uniasr/speech_UniASR_asr_2pass-he-16k-common-vocab1085-pytorch/infer.py

@@ -4,10 +4,10 @@ from modelscope.utils.constant import Tasks
 if __name__ == "__main__":
     audio_in = "https://isv-data.oss-cn-hangzhou.aliyuncs.com/ics/MaaS/ASR/test_audio/asr_example_he.wav"
     output_dir = "./results"
-    inference_pipline = pipeline(
+    inference_pipeline = pipeline(
         task=Tasks.auto_speech_recognition,
         model="damo/speech_UniASR_asr_2pass-he-16k-common-vocab1085-pytorch",
         output_dir=output_dir,
     )
-    rec_result = inference_pipline(audio_in=audio_in, param_dict={"decoding_model":"offline"})
+    rec_result = inference_pipeline(audio_in=audio_in, param_dict={"decoding_model":"offline"})
     print(rec_result)

egs_modelscope/asr/uniasr/speech_UniASR_asr_2pass-id-16k-common-vocab1067-tensorflow1-offline/infer.py

@@ -4,10 +4,10 @@ from modelscope.utils.constant import Tasks
 if __name__ == "__main__":
     audio_in = "https://isv-data.oss-cn-hangzhou.aliyuncs.com/ics/MaaS/ASR/test_audio/asr_example_id.wav"
     output_dir = "./results"
-    inference_pipline = pipeline(
+    inference_pipeline = pipeline(
         task=Tasks.auto_speech_recognition,
         model="damo/speech_UniASR_asr_2pass-id-16k-common-vocab1067-tensorflow1-online",
         output_dir=output_dir,
     )
-    rec_result = inference_pipline(audio_in=audio_in, param_dict={"decoding_model":"offline"})
+    rec_result = inference_pipeline(audio_in=audio_in, param_dict={"decoding_model":"offline"})
     print(rec_result)

egs_modelscope/asr/uniasr/speech_UniASR_asr_2pass-id-16k-common-vocab1067-tensorflow1-online/infer.py

@@ -4,10 +4,10 @@ from modelscope.utils.constant import Tasks
 if __name__ == "__main__":
     audio_in = "https://isv-data.oss-cn-hangzhou.aliyuncs.com/ics/MaaS/ASR/test_audio/asr_example_id.wav"
     output_dir = "./results"
-    inference_pipline = pipeline(
+    inference_pipeline = pipeline(
         task=Tasks.auto_speech_recognition,
         model="damo/speech_UniASR_asr_2pass-id-16k-common-vocab1067-tensorflow1-online",
         output_dir=output_dir,
     )
-    rec_result = inference_pipline(audio_in=audio_in, param_dict={"decoding_model":"normal"})
+    rec_result = inference_pipeline(audio_in=audio_in, param_dict={"decoding_model":"normal"})
     print(rec_result)

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

@@ -4,10 +4,10 @@ from modelscope.utils.constant import Tasks
 if __name__ == "__main__":
     audio_in = "https://isv-data.oss-cn-hangzhou.aliyuncs.com/ics/MaaS/ASR/test_audio/asr_example_ja.wav"
     output_dir = "./results"
-    inference_pipline = pipeline(
+    inference_pipeline = pipeline(
         task=Tasks.auto_speech_recognition,
         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"})
+    rec_result = inference_pipeline(audio_in=audio_in, param_dict={"decoding_model":"offline"})
     print(rec_result)

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

@@ -4,10 +4,10 @@ from modelscope.utils.constant import Tasks
 if __name__ == "__main__":
     audio_in = "https://isv-data.oss-cn-hangzhou.aliyuncs.com/ics/MaaS/ASR/test_audio/asr_example_ja.wav"
     output_dir = "./results"
-    inference_pipline = pipeline(
+    inference_pipeline = pipeline(
         task=Tasks.auto_speech_recognition,
         model="damo/speech_UniASR_asr_2pass-ja-16k-common-vocab93-tensorflow1-online",
         output_dir=output_dir,
     )
-    rec_result = inference_pipline(audio_in=audio_in, param_dict={"decoding_model":"normal"})
+    rec_result = inference_pipeline(audio_in=audio_in, param_dict={"decoding_model":"normal"})
     print(rec_result)

egs_modelscope/asr/uniasr/speech_UniASR_asr_2pass-ko-16k-common-vocab6400-tensorflow1-offline/infer.py

@@ -4,10 +4,10 @@ from modelscope.utils.constant import Tasks
 if __name__ == "__main__":
     audio_in = "https://isv-data.oss-cn-hangzhou.aliyuncs.com/ics/MaaS/ASR/test_audio/asr_example_ko.wav"
     output_dir = "./results"
-    inference_pipline = pipeline(
+    inference_pipeline = pipeline(
         task=Tasks.auto_speech_recognition,
         model="damo/speech_UniASR_asr_2pass-ko-16k-common-vocab6400-tensorflow1-offline",
         output_dir=output_dir,
     )
-    rec_result = inference_pipline(audio_in=audio_in, param_dict={"decoding_model":"offline"})
+    rec_result = inference_pipeline(audio_in=audio_in, param_dict={"decoding_model":"offline"})
     print(rec_result)

egs_modelscope/asr/uniasr/speech_UniASR_asr_2pass-ko-16k-common-vocab6400-tensorflow1-online/infer.py

@@ -4,10 +4,10 @@ from modelscope.utils.constant import Tasks
 if __name__ == "__main__":
     audio_in = "https://isv-data.oss-cn-hangzhou.aliyuncs.com/ics/MaaS/ASR/test_audio/asr_example_ko.wav"
     output_dir = "./results"
-    inference_pipline = pipeline(
+    inference_pipeline = pipeline(
         task=Tasks.auto_speech_recognition,
         model="damo/speech_UniASR_asr_2pass-ko-16k-common-vocab6400-tensorflow1-online",
         output_dir=output_dir,
     )
-    rec_result = inference_pipline(audio_in=audio_in, param_dict={"decoding_model":"normal"})
+    rec_result = inference_pipeline(audio_in=audio_in, param_dict={"decoding_model":"normal"})
     print(rec_result)

egs_modelscope/asr/uniasr/speech_UniASR_asr_2pass-my-16k-common-vocab696-pytorch/infer.py

@@ -4,10 +4,10 @@ from modelscope.utils.constant import Tasks
 if __name__ == "__main__":
     audio_in = "https://isv-data.oss-cn-hangzhou.aliyuncs.com/ics/MaaS/ASR/test_audio/asr_example_my.wav"
     output_dir = "./results"
-    inference_pipline = pipeline(
+    inference_pipeline = pipeline(
         task=Tasks.auto_speech_recognition,
         model="damo/speech_UniASR_asr_2pass-my-16k-common-vocab696-pytorch",
         output_dir=output_dir,
     )
-    rec_result = inference_pipline(audio_in=audio_in, param_dict={"decoding_model":"offline"})
+    rec_result = inference_pipeline(audio_in=audio_in, param_dict={"decoding_model":"offline"})
     print(rec_result)

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

@@ -4,10 +4,10 @@ from modelscope.utils.constant import Tasks
 if __name__ == "__main__":
     audio_in = "https://isv-data.oss-cn-hangzhou.aliyuncs.com/ics/MaaS/ASR/test_audio/asr_example_pt.wav"
     output_dir = "./results"
-    inference_pipline = pipeline(
+    inference_pipeline = pipeline(
         task=Tasks.auto_speech_recognition,
         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"})
+    rec_result = inference_pipeline(audio_in=audio_in, param_dict={"decoding_model":"offline"})
     print(rec_result)

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

@@ -4,10 +4,10 @@ from modelscope.utils.constant import Tasks
 if __name__ == "__main__":
     audio_in = "https://isv-data.oss-cn-hangzhou.aliyuncs.com/ics/MaaS/ASR/test_audio/asr_example_pt.wav"
     output_dir = "./results"
-    inference_pipline = pipeline(
+    inference_pipeline = pipeline(
         task=Tasks.auto_speech_recognition,
         model="damo/speech_UniASR_asr_2pass-pt-16k-common-vocab1617-tensorflow1-online",
         output_dir=output_dir,
     )
-    rec_result = inference_pipline(audio_in=audio_in, param_dict={"decoding_model":"normal"})
+    rec_result = inference_pipeline(audio_in=audio_in, param_dict={"decoding_model":"normal"})
     print(rec_result)

egs_modelscope/asr/uniasr/speech_UniASR_asr_2pass-ru-16k-common-vocab1664-tensorflow1-offline/infer.py

@@ -4,10 +4,10 @@ from modelscope.utils.constant import Tasks
 if __name__ == "__main__":
     audio_in = "https://isv-data.oss-cn-hangzhou.aliyuncs.com/ics/MaaS/ASR/test_audio/asr_example_ru.wav"
     output_dir = "./results"
-    inference_pipline = pipeline(
+    inference_pipeline = pipeline(
         task=Tasks.auto_speech_recognition,
         model="damo/speech_UniASR_asr_2pass-ru-16k-common-vocab1664-tensorflow1-offline",
         output_dir=output_dir,
     )
-    rec_result = inference_pipline(audio_in=audio_in, param_dict={"decoding_model":"offline"})
+    rec_result = inference_pipeline(audio_in=audio_in, param_dict={"decoding_model":"offline"})
     print(rec_result)

egs_modelscope/asr/uniasr/speech_UniASR_asr_2pass-ru-16k-common-vocab1664-tensorflow1-online/infer.py

@@ -4,10 +4,10 @@ from modelscope.utils.constant import Tasks
 if __name__ == "__main__":
     audio_in = "https://isv-data.oss-cn-hangzhou.aliyuncs.com/ics/MaaS/ASR/test_audio/asr_example_ru.wav"
     output_dir = "./results"
-    inference_pipline = pipeline(
+    inference_pipeline = pipeline(
         task=Tasks.auto_speech_recognition,
         model="damo/speech_UniASR_asr_2pass-ru-16k-common-vocab1664-tensorflow1-online",
         output_dir=output_dir,
     )
-    rec_result = inference_pipline(audio_in=audio_in, param_dict={"decoding_model":"normal"})
+    rec_result = inference_pipeline(audio_in=audio_in, param_dict={"decoding_model":"normal"})
     print(rec_result)

egs_modelscope/asr/uniasr/speech_UniASR_asr_2pass-ur-16k-common-vocab877-pytorch/infer.py

@@ -4,10 +4,10 @@ from modelscope.utils.constant import Tasks
 if __name__ == "__main__":
     audio_in = "https://isv-data.oss-cn-hangzhou.aliyuncs.com/ics/MaaS/ASR/test_audio/asr_example_ur.wav"
     output_dir = "./results"
-    inference_pipline = pipeline(
+    inference_pipeline = pipeline(
         task=Tasks.auto_speech_recognition,
         model="damo/speech_UniASR_asr_2pass-ur-16k-common-vocab877-pytorch",
         output_dir=output_dir,
     )
-    rec_result = inference_pipline(audio_in=audio_in, param_dict={"decoding_model":"offline"})
+    rec_result = inference_pipeline(audio_in=audio_in, param_dict={"decoding_model":"offline"})
     print(rec_result)

egs_modelscope/asr/uniasr/speech_UniASR_asr_2pass-vi-16k-common-vocab1001-pytorch-offline/infer.py

@@ -4,10 +4,10 @@ from modelscope.utils.constant import Tasks
 if __name__ == "__main__":
     audio_in = "https://isv-data.oss-cn-hangzhou.aliyuncs.com/ics/MaaS/ASR/test_audio/asr_example_vi.wav"
     output_dir = "./results"
-    inference_pipline = pipeline(
+    inference_pipeline = pipeline(
         task=Tasks.auto_speech_recognition,
         model="damo/speech_UniASR_asr_2pass-vi-16k-common-vocab1001-pytorch-offline",
         output_dir=output_dir,
     )
-    rec_result = inference_pipline(audio_in=audio_in, param_dict={"decoding_model":"offline"})
+    rec_result = inference_pipeline(audio_in=audio_in, param_dict={"decoding_model":"offline"})
     print(rec_result)

egs_modelscope/asr/uniasr/speech_UniASR_asr_2pass-vi-16k-common-vocab1001-pytorch-online/infer.py

@@ -4,10 +4,10 @@ from modelscope.utils.constant import Tasks
 if __name__ == "__main__":
     audio_in = "https://isv-data.oss-cn-hangzhou.aliyuncs.com/ics/MaaS/ASR/test_audio/asr_example_vi.wav"
     output_dir = "./results"
-    inference_pipline = pipeline(
+    inference_pipeline = pipeline(
         task=Tasks.auto_speech_recognition,
         model="damo/speech_UniASR_asr_2pass-vi-16k-common-vocab1001-pytorch-online",
         output_dir=output_dir,
     )
-    rec_result = inference_pipline(audio_in=audio_in, param_dict={"decoding_model":"normal"})
+    rec_result = inference_pipeline(audio_in=audio_in, param_dict={"decoding_model":"normal"})
     print(rec_result)

egs_modelscope/asr/uniasr/speech_UniASR_asr_2pass-zh-cn-16k-common-vocab8358-tensorflow1-offline/infer.py

@@ -4,11 +4,11 @@ from modelscope.utils.constant import Tasks
 if __name__ == '__main__':
     audio_in = 'https://isv-data.oss-cn-hangzhou.aliyuncs.com/ics/MaaS/ASR/test_audio/asr_example_zh.wav'
     output_dir = None
-    inference_pipline = pipeline(
+    inference_pipeline = pipeline(
         task=Tasks.auto_speech_recognition,
         model="damo/speech_UniASR_asr_2pass-zh-cn-16k-common-vocab8358-tensorflow1-offline",
         output_dir=output_dir,
     )
-    rec_result = inference_pipline(audio_in=audio_in)
+    rec_result = inference_pipeline(audio_in=audio_in)
     print(rec_result)
 

egs_modelscope/asr/uniasr/speech_UniASR_asr_2pass-zh-cn-16k-common-vocab8358-tensorflow1-online/infer.py

@@ -4,11 +4,11 @@ from modelscope.utils.constant import Tasks
 if __name__ == '__main__':
     audio_in = 'https://isv-data.oss-cn-hangzhou.aliyuncs.com/ics/MaaS/ASR/test_audio/asr_example_zh.wav'
     output_dir = None
-    inference_pipline = pipeline(
+    inference_pipeline = pipeline(
         task=Tasks.auto_speech_recognition,
         model="damo/speech_UniASR_asr_2pass-zh-cn-16k-common-vocab8358-tensorflow1-online",
         output_dir=output_dir,
     )
-    rec_result = inference_pipline(audio_in=audio_in)
+    rec_result = inference_pipeline(audio_in=audio_in)
     print(rec_result)
 

egs_modelscope/asr/uniasr/speech_UniASR_asr_2pass-zh-cn-8k-common-vocab3445-pytorch-offline/infer.py

@@ -16,14 +16,14 @@ def modelscope_infer_core(output_dir, split_dir, njob, idx):
         os.environ['CUDA_VISIBLE_DEVICES'] = str(gpu_list[gpu_id])
     else:
         os.environ['CUDA_VISIBLE_DEVICES'] = str(gpu_id)
-    inference_pipline = pipeline(
+    inference_pipeline = pipeline(
         task=Tasks.auto_speech_recognition,
         model="damo/speech_UniASR_asr_2pass-zh-cn-8k-common-vocab3445-pytorch-offline",
         output_dir=output_dir_job,
         batch_size=1
     )
     audio_in = os.path.join(split_dir, "wav.{}.scp".format(idx))
-    inference_pipline(audio_in=audio_in)
+    inference_pipeline(audio_in=audio_in)
 
 def modelscope_infer(params):
     # prepare for multi-GPU decoding

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

@@ -16,14 +16,14 @@ def modelscope_infer_core(output_dir, split_dir, njob, idx):
         os.environ['CUDA_VISIBLE_DEVICES'] = str(gpu_list[gpu_id])
     else:
         os.environ['CUDA_VISIBLE_DEVICES'] = str(gpu_id)
-    inference_pipline = pipeline(
+    inference_pipeline = pipeline(
         task=Tasks.auto_speech_recognition,
         model="damo/speech_UniASR_asr_2pass-zh-cn-8k-common-vocab3445-pytorch-online",
         output_dir=output_dir_job,
         batch_size=1
     )
     audio_in = os.path.join(split_dir, "wav.{}.scp".format(idx))
-    inference_pipline(audio_in=audio_in, param_dict={"decoding_model": "normal"})
+    inference_pipeline(audio_in=audio_in, param_dict={"decoding_model": "normal"})
 
 
 def modelscope_infer(params):

egs_modelscope/asr/uniasr/speech_UniASR_asr_2pass-zh-cn-8k-common-vocab8358-tensorflow1-offline/infer.py

@@ -4,11 +4,11 @@ from modelscope.utils.constant import Tasks
 if __name__ == '__main__':
     audio_in = 'https://isv-data.oss-cn-hangzhou.aliyuncs.com/ics/MaaS/ASR/test_audio/asr_example_zh.wav'
     output_dir = None
-    inference_pipline = pipeline(
+    inference_pipeline = pipeline(
         task=Tasks.auto_speech_recognition,
         model="damo/speech_UniASR_asr_2pass-zh-cn-8k-common-vocab8358-tensorflow1-offline",
         output_dir=output_dir,
     )
-    rec_result = inference_pipline(audio_in=audio_in)
+    rec_result = inference_pipeline(audio_in=audio_in)
     print(rec_result)
 

egs_modelscope/asr/uniasr/speech_UniASR_asr_2pass-zh-cn-8k-common-vocab8358-tensorflow1-online/infer.py

@@ -4,11 +4,11 @@ from modelscope.utils.constant import Tasks
 if __name__ == '__main__':
     audio_in = 'https://isv-data.oss-cn-hangzhou.aliyuncs.com/ics/MaaS/ASR/test_audio/asr_example_zh.wav'
     output_dir = None
-    inference_pipline = pipeline(
+    inference_pipeline = pipeline(
         task=Tasks.auto_speech_recognition,
         model="damo/speech_UniASR_asr_2pass-zh-cn-8k-common-vocab8358-tensorflow1-online",
         output_dir=output_dir,
     )
-    rec_result = inference_pipline(audio_in=audio_in)
+    rec_result = inference_pipeline(audio_in=audio_in)
     print(rec_result)
 

egs_modelscope/lm/speech_transformer_lm_zh-cn-common-vocab8404-pytorch/infer.py

@@ -6,12 +6,12 @@ inputs = "hello 大 家 好 呀"
 from modelscope.pipelines import pipeline
 from modelscope.utils.constant import Tasks
 
-inference_pipline = pipeline(
+inference_pipeline = pipeline(
     task=Tasks.language_score_prediction,
     model='damo/speech_transformer_lm_zh-cn-common-vocab8404-pytorch',
     output_dir="./tmp/"
 )
 
-rec_result = inference_pipline(text_in=inputs)
+rec_result = inference_pipeline(text_in=inputs)
 print(rec_result)
 

egs_modelscope/punctuation/TEMPLATE/README.md

@@ -11,21 +11,21 @@
 from modelscope.pipelines import pipeline
 from modelscope.utils.constant import Tasks
 
-inference_pipline = pipeline(
+inference_pipeline = pipeline(
     task=Tasks.punctuation,
     model='damo/punc_ct-transformer_zh-cn-common-vocab272727-pytorch',
     model_revision=None)
 
-rec_result = inference_pipline(text_in='example/punc_example.txt')
+rec_result = inference_pipeline(text_in='example/punc_example.txt')
 print(rec_result)
 ```
 - text二进制数据，例如：用户直接从文件里读出bytes数据
 ```python
-rec_result = inference_pipline(text_in='我们都是木头人不会讲话不会动')
+rec_result = inference_pipeline(text_in='我们都是木头人不会讲话不会动')
 ```
 - text文件url，例如：https://isv-data.oss-cn-hangzhou.aliyuncs.com/ics/MaaS/ASR/test_text/punc_example.txt
 ```python
-rec_result = inference_pipline(text_in='https://isv-data.oss-cn-hangzhou.aliyuncs.com/ics/MaaS/ASR/test_text/punc_example.txt')
+rec_result = inference_pipeline(text_in='https://isv-data.oss-cn-hangzhou.aliyuncs.com/ics/MaaS/ASR/test_text/punc_example.txt')
 ```
 
 #### [CT-Transformer Realtime model](https://www.modelscope.cn/models/damo/punc_ct-transformer_zh-cn-common-vad_realtime-vocab272727/summary)

egs_modelscope/punctuation/punc_ct-transformer_zh-cn-common-vocab272727-pytorch/demo.py

@@ -12,12 +12,12 @@ inputs = "./egs_modelscope/punctuation/punc_ct-transformer_zh-cn-common-vocab272
 from modelscope.pipelines import pipeline
 from modelscope.utils.constant import Tasks
 
-inference_pipline = pipeline(
+inference_pipeline = pipeline(
     task=Tasks.punctuation,
     model='damo/punc_ct-transformer_zh-cn-common-vocab272727-pytorch',
     model_revision="v1.1.7",
     output_dir="./tmp/"
 )
 
-rec_result = inference_pipline(text_in=inputs)
+rec_result = inference_pipeline(text_in=inputs)
 print(rec_result)

egs_modelscope/tp/TEMPLATE/README.md

@@ -8,12 +8,12 @@
 from modelscope.pipelines import pipeline
 from modelscope.utils.constant import Tasks
 
-inference_pipline = pipeline(
+inference_pipeline = pipeline(
     task=Tasks.speech_timestamp,
     model='damo/speech_timestamp_prediction-v1-16k-offline',
     output_dir=None)
 
-rec_result = inference_pipline(
+rec_result = inference_pipeline(
     audio_in='https://isv-data.oss-cn-hangzhou.aliyuncs.com/ics/MaaS/ASR/test_audio/asr_example_timestamps.wav',
     text_in='一 个 东 太 平 洋 国 家 为 什 么 跑 到 西 太 平 洋 来 了 呢',)
 print(rec_result)

egs_modelscope/tp/speech_timestamp_prediction-v1-16k-offline/demo.py

@@ -1,12 +1,12 @@
 from modelscope.pipelines import pipeline
 from modelscope.utils.constant import Tasks
 
-inference_pipline = pipeline(
+inference_pipeline = pipeline(
     task=Tasks.speech_timestamp,
     model='damo/speech_timestamp_prediction-v1-16k-offline',
     output_dir=None)
 
-rec_result = inference_pipline(
+rec_result = inference_pipeline(
     audio_in='https://isv-data.oss-cn-hangzhou.aliyuncs.com/ics/MaaS/ASR/test_audio/asr_example_timestamps.wav',
     text_in='一 个 东 太 平 洋 国 家 为 什 么 跑 到 西 太 平 洋 来 了 呢',)
 print(rec_result)

egs_modelscope/vad/speech_fsmn_vad_zh-cn-16k-common/demo.py

@@ -4,12 +4,12 @@ from modelscope.utils.constant import Tasks
 if __name__ == '__main__':
     audio_in = 'https://isv-data.oss-cn-hangzhou.aliyuncs.com/ics/MaaS/ASR/test_audio/vad_example.wav'
     output_dir = None
-    inference_pipline = pipeline(
+    inference_pipeline = pipeline(
         task=Tasks.voice_activity_detection,
         model="damo/speech_fsmn_vad_zh-cn-16k-common-pytorch",
         model_revision='v1.2.0',
         output_dir=output_dir,
         batch_size=1,
     )
-    segments_result = inference_pipline(audio_in=audio_in)
+    segments_result = inference_pipeline(audio_in=audio_in)
     print(segments_result)

egs_modelscope/vad/speech_fsmn_vad_zh-cn-16k-common/demo_online.py

@@ -8,7 +8,7 @@ import soundfile
 
 if __name__ == '__main__':
     output_dir = None
-    inference_pipline = pipeline(
+    inference_pipeline = pipeline(
         task=Tasks.voice_activity_detection,
         model="damo/speech_fsmn_vad_zh-cn-16k-common-pytorch",
         model_revision='v1.2.0',
@@ -30,7 +30,7 @@ if __name__ == '__main__':
         else:
             is_final = False
         param_dict['is_final'] = is_final
-        segments_result = inference_pipline(audio_in=speech[sample_offset: sample_offset + step],
+        segments_result = inference_pipeline(audio_in=speech[sample_offset: sample_offset + step],
                                             param_dict=param_dict)
         print(segments_result)
 

egs_modelscope/vad/speech_fsmn_vad_zh-cn-8k-common/demo.py

@@ -4,12 +4,12 @@ from modelscope.utils.constant import Tasks
 if __name__ == '__main__':
     audio_in = 'https://isv-data.oss-cn-hangzhou.aliyuncs.com/ics/MaaS/ASR/test_audio/vad_example_8k.wav'
     output_dir = None
-    inference_pipline = pipeline(
+    inference_pipeline = pipeline(
         task=Tasks.voice_activity_detection,
         model="damo/speech_fsmn_vad_zh-cn-8k-common",
         model_revision='v1.2.0',
         output_dir=output_dir,
         batch_size=1,
     )
-    segments_result = inference_pipline(audio_in=audio_in)
+    segments_result = inference_pipeline(audio_in=audio_in)
     print(segments_result)

egs_modelscope/vad/speech_fsmn_vad_zh-cn-8k-common/demo_online.py

@@ -8,7 +8,7 @@ import soundfile
 
 if __name__ == '__main__':
     output_dir = None
-    inference_pipline = pipeline(
+    inference_pipeline = pipeline(
         task=Tasks.voice_activity_detection,
         model="damo/speech_fsmn_vad_zh-cn-8k-common",
         model_revision='v1.2.0',
@@ -30,7 +30,7 @@ if __name__ == '__main__':
         else:
             is_final = False
         param_dict['is_final'] = is_final
-        segments_result = inference_pipline(audio_in=speech[sample_offset: sample_offset + step],
+        segments_result = inference_pipeline(audio_in=speech[sample_offset: sample_offset + step],
                                             param_dict=param_dict)
         print(segments_result)