Update app.py

app.py

@@ -111,12 +111,19 @@ def predict_emotion(audio_file, use_ensemble=False, apply_noise_reduction=False,
             label = ensemble_prediction(audio_file, apply_noise_reduction, segment_duration, overlap)
         else:
             temp_file = preprocess_audio(audio_file, apply_noise_reduction)
-            _, _, _, label = classifier.classify_file(temp_file)
+            result = classifier.classify_file(temp_file)  # Check if this returns a list
             os.remove(temp_file)
-        return add_emoji_to_label(label)
+
+            if isinstance(result, list):  # Ensure we extract the correct label
+                label = result[-1]  # Assuming the last item is the label
+            else:
+                label = result
+
+        return add_emoji_to_label(str(label))  # Convert to string before .lower()
     except Exception as e:
         return f"Error processing file: {str(e)}"
 
+
 def plot_waveform(audio_file):
     """
     Generate and return a waveform plot image (as a PIL Image) for the given audio file.