diff --git a/README.md b/README.md
index 455c064..c186644 100644
--- a/README.md
+++ b/README.md
@@ -11,7 +11,7 @@ Each vector represents for an audio clip with a fixed length of around 1s.
 This operator generates audio embeddings with fingerprinting method introduced by [Neural Audio Fingerprint](https://arxiv.org/abs/2010.11910).
 The model is implemented in Pytorch.
 We've also trained the nnfp model with [FMA dataset](https://github.com/mdeff/fma) (& some noise audio) and shared weights in this operator.
-The nnfp operator is suitable to generate audio fingerprints.
+The nnfp operator is suitable for audio fingerprinting.
 
 <br />
 
@@ -84,7 +84,7 @@ An audio embedding operator generates vectors in numpy.ndarray given towhee audi
 *data: List[towhee.types.audio_frame.AudioFrame]*
 
 Input audio data is a list of towhee audio frames.
-The input data should represent for an audio longer than 1s.
+The audio input should be at least 1s.
 
 
 **Returns**: