diff --git a/tests/test_asr_inference_pipeline.py b/tests/test_asr_inference_pipeline.py
index 6257d114c..70dbe8952 100644
--- a/tests/test_asr_inference_pipeline.py
+++ b/tests/test_asr_inference_pipeline.py
@@ -65,7 +65,7 @@ class TestMfccaInferencePipelines(unittest.TestCase):
             model='NPU-ASLP/speech_mfcca_asr-zh-cn-16k-alimeeting-vocab4950',
             model_revision='v3.0.0')
         rec_result = inference_pipeline(
-            audio_in='16:32https://pre.modelscope.cn/api/v1/models/NPU-ASLP/speech_mfcca_asr-zh-cn-16k-alimeeting-vocab4950/repo?Revision=master&FilePath=example/asr_example_mc.wav')
+            audio_in='https://pre.modelscope.cn/api/v1/models/NPU-ASLP/speech_mfcca_asr-zh-cn-16k-alimeeting-vocab4950/repo?Revision=master&FilePath=example/asr_example_mc.wav')
         logger.info("asr inference result: {0}".format(rec_result))
 
 
@@ -451,8 +451,8 @@ class TestUniasrInferencePipelines(unittest.TestCase):
 
     def test_uniasr_2pass_zhcn_16k_common_vocab8358_offline(self):
         inference_pipeline = pipeline(
-            task=Tasks.auto_speech_recognition,
-            model='damo/speech_UniASR_asr_2pass-zh-cn-16k-common-vocab8358-tensorflow1-offline')
+            task=Tasks.,
+            model='damo/speech_UniASauto_speech_recognitionR_asr_2pass-zh-cn-16k-common-vocab8358-tensorflow1-offline')
         rec_result = inference_pipeline(
             audio_in='https://isv-data.oss-cn-hangzhou.aliyuncs.com/ics/MaaS/ASR/test_audio/asr_example_zh.wav',
             param_dict={"decoding_model": "offline"})
diff --git a/tests/test_asr_vad_punc_inference_pipeline.py b/tests/test_asr_vad_punc_inference_pipeline.py
new file mode 100644
index 000000000..bcb57e09f
--- /dev/null
+++ b/tests/test_asr_vad_punc_inference_pipeline.py
@@ -0,0 +1,32 @@
+import unittest
+
+from modelscope.pipelines import pipeline
+from modelscope.utils.constant import Tasks
+from modelscope.utils.logger import get_logger
+
+logger = get_logger()
+
+class TestParaformerInferencePipelines(unittest.TestCase):
+    def test_funasr_path(self):
+        import funasr
+        import os
+        logger.info("run_dir:{0} ; funasr_path: {1}".format(os.getcwd(), funasr.__file__))
+
+    def test_inference_pipeline(self):
+        inference_pipeline = pipeline(
+            task=Tasks.auto_speech_recognition,
+            model='damo/speech_paraformer-large-vad-punc_asr_nat-zh-cn-16k-common-vocab8404-pytorch',
+            model_revision="v1.2.1",
+            vad_model='damo/speech_fsmn_vad_zh-cn-16k-common-pytorch',
+            vad_model_revision="v1.1.8",
+            punc_model='damo/punc_ct-transformer_zh-cn-common-vocab272727-pytorch',
+            punc_model_revision="v1.1.6",
+            ngpu=1,
+        )
+        rec_result = inference_pipeline(
+            audio_in='https://isv-data.oss-cn-hangzhou.aliyuncs.com/ics/MaaS/ASR/test_audio/asr_example_zh.wav')
+        logger.info("asr inference result: {0}".format(rec_result))
+
+
+if __name__ == '__main__':
+    unittest.main()