Update app.py

app.py

@@ -57,13 +57,13 @@ def convert_to_wav(audio_file):
 #:::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::
 asr = pipeline("automatic-speech-recognition", "NbAiLabBeta/nb-whisper-large")
 
-def transcribe_audio(audio_file, batch_size=16):
+def transcribe_audio(audio_file, batch_size=4):
     if audio_file.endswith(".m4a"):
         audio_file = convert_to_wav(audio_file)
         
     start_time = time.time()
 
-    outputs = asr(audio_file, chunk_length_s=28, return_timestamps=False, generate_kwargs={'num_beams': 5, 'task': 'transcribe', 'language': 'no'}) 
+    outputs = asr(audio_file, chunk_length_s=28, batch_size=batch_size, return_timestamps=False, generate_kwargs={'num_beams': 5, 'task': 'transcribe', 'language': 'no'}, skip_special_tokens=True) 
     text = outputs["text"]
 
     end_time = time.time()