add infer aishell1 subtest demo in paraformer-large-contextual

egs_modelscope/asr/paraformer/speech_paraformer-large-contextual_asr_nat-zh-cn-16k-common-vocab8404/infer.py

@@ -6,7 +6,7 @@ if __name__ == '__main__':
     param_dict = dict()
     param_dict['hotword'] = "https://isv-data.oss-cn-hangzhou.aliyuncs.com/ics/MaaS/ASR/test_audio/hotword.txt"
 
-    audio_in = "//isv-data.oss-cn-hangzhou.aliyuncs.com/ics/MaaS/ASR/test_audio/asr_example_hotword.wav"
+    audio_in = "https://isv-data.oss-cn-hangzhou.aliyuncs.com/ics/MaaS/ASR/test_audio/asr_example_hotword.wav"
     output_dir = None
     batch_size = 1
 

egs_modelscope/asr/paraformer/speech_paraformer-large-contextual_asr_nat-zh-cn-16k-common-vocab8404/infer_aishell1_subtest_demo.py

@@ -0,0 +1,36 @@
+import os
+import tempfile
+import codecs
+from modelscope.pipelines import pipeline
+from modelscope.utils.constant import Tasks
+from modelscope.msdatasets import MsDataset
+
+if __name__ == '__main__':
+    param_dict = dict()
+    param_dict['hotword'] = "https://isv-data.oss-cn-hangzhou.aliyuncs.com/ics/MaaS/ASR/test_audio/hotword.txt"
+
+    output_dir = "./output"
+    batch_size = 1
+
+    # dataset split ['test']
+    ds_dict = MsDataset.load(dataset_name='speech_asr_aishell1_hotwords_testsets', namespace='speech_asr')
+    work_dir = tempfile.TemporaryDirectory().name
+    if not os.path.exists(work_dir):
+        os.makedirs(work_dir)
+    wav_file_path = os.path.join(work_dir, "wav.scp")
+    
+    with codecs.open(wav_file_path, 'w') as fin: 
+        for line in ds_dict:
+            wav = line["Audio:FILE"]
+            idx = wav.split("/")[-1].split(".")[0]
+            fin.writelines(idx + " " + wav + "\n")
+    audio_in = wav_file_path         
+
+    inference_pipeline = pipeline(
+        task=Tasks.auto_speech_recognition,
+        model="damo/speech_paraformer-large-contextual_asr_nat-zh-cn-16k-common-vocab8404",
+        output_dir=output_dir,
+        batch_size=batch_size,
+        param_dict=param_dict)
+
+    rec_result = inference_pipeline(audio_in=audio_in)