Update app.py

app.py

@@ -265,39 +265,39 @@ def process_document(file):
 
 # Function to handle speech-to-text conversion
 
-#def transcribe_audio(audio):
-    sr, y = audio
-    if y.ndim > 1:
-        y = y.mean(axis=1)
-    y = y.astype(np.float32)
-    y /= np.max(np.abs(y))
-    return transcriber({"sampling_rate": sr, "raw": y})["text"]
-
-"""
-#Quick Fixes You Can Try First:
-
 #def transcribe_audio(audio):
 #    sr, y = audio
 #    if y.ndim > 1:
 #        y = y.mean(axis=1)
 #    y = y.astype(np.float32)
+#    y /= np.max(np.abs(y))
+#    return transcriber({"sampling_rate": sr, "raw": y})["text"]
+
+
+#Quick Fixes You Can Try First:
+
+def transcribe_audio(audio):
+    sr, y = audio
+    if y.ndim > 1:
+        y = y.mean(axis=1)
+    y = y.astype(np.float32)
     
     # Improved normalization
-#    max_val = np.max(np.abs(y))
-#    if max_val > 0:
-#        y /= max_val
+    max_val = np.max(np.abs(y))
+    if max_val > 0:
+        y /= max_val
     
     # Use better model
-#    better_transcriber = pipeline(
-#        "automatic-speech-recognition",
-#        model="openai/whisper-small.en",  # More accurate
-#        chunk_length_s=30
-#    )
+    better_transcriber = pipeline(
+        "automatic-speech-recognition",
+        model="openai/whisper-small.en",  # More accurate
+        chunk_length_s=30
+    )
     
-#    return better_transcriber({"sampling_rate": sr, "raw": y})["text"]
+    return better_transcriber({"sampling_rate": sr, "raw": y})["text"]
 
 # the remaining is the same 
-"""
+