Update app.py

app.py

@@ -56,9 +56,7 @@ def classify_toxicity(audio_file, selected_sounds, slider):
         transcribed_text = pipe(audio_file)["text"]
     else:
         transcribed_text = text_input
-
-    selected_class_names = selected_sounds.split(",")
-    
+        
     threshold = slider_logic(slider)
     model = whisper.load_model("large")
     # model = model_cache[model_name]
@@ -92,7 +90,8 @@ def classify_toxicity(audio_file, selected_sounds, slider):
     scores = average_logprobs.softmax(-1).tolist()
     
     class_score_dict = {class_name: score for class_name, score in zip(class_names, scores)}
-    for selected_class_name in selected_class_names:
+    
+    for selected_class_name in selected_sounds:
         if selected_class_name in class_score_dict:
             score = class_score_dict[selected_class_name]
             if score > threshold: