diff --git a/egs/librispeech/ASR/transducer_emformer/streaming_feature_extractor.py b/egs/librispeech/ASR/transducer_emformer/streaming_feature_extractor.py
index c3d9a5675..4d405cad1 100644
--- a/egs/librispeech/ASR/transducer_emformer/streaming_feature_extractor.py
+++ b/egs/librispeech/ASR/transducer_emformer/streaming_feature_extractor.py
@@ -14,10 +14,11 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
+from typing import List, Optional
+
+import torch
 from beam_search import HypothesisList
 from kaldifeat import FbankOptions, OnlineFbank, OnlineFeature
-from typing import List, Optional
-import torch
 
 
 def _create_streaming_feature_extractor() -> OnlineFeature:
@@ -41,6 +42,15 @@ def _create_streaming_feature_extractor() -> OnlineFeature:
 
 class FeatureExtractionStream(object):
     def __init__(self, context_size: int, decoding_method: str) -> None:
+        """
+        Args:
+          context_size:
+            Context size of the RNN-T decoder model.
+          decoding_method:
+            Decoding method. The possible values are:
+              - greedy_search
+              - modified_beam_search
+        """
         self.feature_extractor = _create_streaming_feature_extractor()
         # It contains a list of 1-D tensors representing the feature frames.
         self.feature_frames: List[torch.Tensor] = []