Update app.py

app.py

@@ -3,10 +3,10 @@ import os
 import torch
 import io
 import wavio
+import numpy as np
 from pyannote.audio import Pipeline
 from pyannote.audio import Audio
 from pyannote.core import Segment
-import numpy as np
 
 pipeline = Pipeline.from_pretrained(
   "pyannote/speaker-diarization-3.1",
@@ -20,7 +20,7 @@ def process_audio(audio):
     audio_data = np.int16(audio_data / np.max(np.abs(audio_data)) * 32767)
     
     # Save the uploaded audio file to a temporary location
-    wavio.write("temp.wav", audio_data, sample_rate, sampwidth=2)
+    wavio.write("temp.wav", audio_data[:, np.newaxis], sample_rate, sampwidth=2)
     
     # Use the diarization pipeline to process the audio
     diarization = pipeline("temp.wav")