Update app.py

app.py

@@ -127,12 +127,12 @@ A CNN predicts a label and confidence score for each chunk.
 The final prediction is determined by:
 1. **Majority vote**, the class predicted most frequently across chunks.  
 2. **Confidence tie-breaker**, if classes tie, the model selects the one with the **highest total confidence** across its chunks.  
-3. **Final confidence** — the average confidence of all chunks belonging to the final class.
+3. **Final confidence**, the average confidence of all chunks belonging to the final class.
 
 The JSON output shows the final label, its confidence, and all per-chunk predictions.
 
 Classes you can classify them:
-. **Baby Cry**
+**Baby Cry**
 . **Chainsaw**
 . **Clock Tick**
 . **Cow**