Update app.py

app.py

@@ -4,9 +4,9 @@ from transformers import Wav2Vec2FeatureExtractor
 from datasets import Dataset
 import librosa
 
-feature_extractor = Wav2Vec2FeatureExtractor.from_pretrained("superb/hubert-large-superb-er")
-
 def get_emotion(microphone, file_upload, task):
+    
+    feature_extractor = Wav2Vec2FeatureExtractor.from_pretrained("superb/hubert-large-superb-er")
     warn_output = ""
     
     if (microphone is not None) and (file_upload is not None):
@@ -17,6 +17,7 @@ def get_emotion(microphone, file_upload, task):
     elif (microphone is None) and (file_upload is None):
         return "ERROR: You have to either use the microphone or upload an audio file"
 
+    
     file = microphone if microphone is not None else file_upload
     test = feature_extractor(file, sampling_rate=16000, padding=True, return_tensors="pt" ).to(torch.float32)       
     logits = model(**test).logits