Update app.py

app.py

@@ -44,7 +44,8 @@ vgg16 = models.vgg16(pretrained=True).features
 def preprocess_single_audio_vgg16(audio_data, sr, vgg16_model, pca_instance):
     # Your existing preprocessing code goes here
     y= audio_data
-    sr = 22050# Load audio
+    sr=sr
+    # Load audio
     mel_spec = librosa.feature.melspectrogram(y=y, sr=sr, n_mels=128)  # Compute Mel spectrogram
     log_mel_spec = librosa.power_to_db(mel_spec, ref=np.max)  # Apply log transformation
     norm_mel_spec = (log_mel_spec - np.mean(log_mel_spec)) / np.std(log_mel_spec)  # Normalize
@@ -80,7 +81,7 @@ def predict_language(audio_input):
     # Load VGG16 model
     if isinstance(audio_input, str):
         # Load the audio file
-      audio, sr = librosa.load(audio_input, sr=None)
+      audio, sr = librosa.load(audio_input, sr=22050)
     else:
         # Get the sample rate and convert the audio data to float
       sr, audio = audio_input