diff --git a/README.md b/README.md
index a3e36d2..885cb6c 100644
--- a/README.md
+++ b/README.md
@@ -12,10 +12,18 @@ The model is pre-trained with a large scale of audio dataset [AudioSet](https://
 As suggested, it is suitable to extract features at high level or warm up a larger model.
 
 ```python
+import numpy as np
 from towhee import ops
 
 audio_encoder = ops.audio_embedding.vggish()
-audio_embedding = audio_encoder("/path/to/audio")
+
+# Path or url as input
+audio_embedding = audio_encoder("/audio/path/or/url/")
+
+# Audio data as input
+audio_data = np.zeros((441344, 2))
+sample_rate = 44100
+audio_embedding = audio_encoder(audio_data, sample_rate)
 ```
 
 ## Factory Constructor
diff --git a/vggish.py b/vggish.py
index 86d327b..dfc3de2 100644
--- a/vggish.py
+++ b/vggish.py
@@ -71,6 +71,11 @@ class Vggish(NNOperator):
 
 # if __name__ == '__main__':
 #     encoder = Vggish()
-#     audio_path = '/path/to/audio'
-#     vec = encoder(audio_path)
+#
+#     # audio_path = '/path/to/audio'
+#     # vec = encoder(audio_path)
+#
+#     audio_data = numpy.zeros((441344, 2))
+#     sample_rate = 44100
+#     vec = encoder(audio_data, sample_rate)
 #     print(vec)