Update app.py

app.py

@@ -33,25 +33,6 @@ EXAMPLES = [
   ["examples/english.wav", "English", True, "Linda", "every window and roof which could command a view of the horrible performance was occupied"],
 ]
 
-def reformat_freq(sr, y):
-    if sr not in (
-        48000,
-        16000,
-    ):  # Deepspeech only supports 16k, (we convert 48k -> 16k)
-        raise ValueError("Unsupported rate", sr)
-    if sr == 48000:
-        y = (
-            ((y / max(np.max(y), 1)) * 32767)
-            .reshape((-1, 3))
-            .mean(axis=1)
-            .astype("int16")
-        )
-        sr = 16000
-    return sr, y
-
-
-
-
 def stt_record(audio_record_buffer):
     #using english model, it is here to reduce memory usage, will trigger download first run
     #unfortunately will be slow as it is shared cpu/memory need to free memory after run
@@ -60,9 +41,11 @@ def stt_record(audio_record_buffer):
 
     if type(audio_record_buffer)!=tuple:
         y, sr = librosa.load(audio_record_buffer)
-        _, y = reformat_freq(sr,y)  
     else:
-        _, y = reformat_freq(*audio_record_buffer)  
+        sr, y = audio_record_buffer
+        
+    y = librosa.resample(y, orig_sr=sr, target_sr=16000)
+    
     scorer = True # use scorer
     if scorer:
         acoustic_model.enableExternalScorer(scorer_path)