Update app.py

app.py

@@ -7,7 +7,7 @@ from sklearn.preprocessing import StandardScaler
 model = joblib.load('UTI.pkl')
 
 def predictor(audio_filename):
-    y,sr = librosa.load(audio_filename)
+    y,sr = librosa.load(audio_filename,mono=True,duration=5)
 
     chroma_stft = np.mean(librosa.feature.chroma_stft(y=y, sr=sr))
     rmse = np.mean(librosa.feature.rms(y=y))