main

app.py

@@ -4,13 +4,10 @@ import pandas as pd
 import torch
 import torchaudio
 import time
-
 from transformers import pipeline
-# from speechbrain.inference.VAD import VAD
 from speechbrain.inference.classifiers import EncoderClassifier
 
 transcriber = pipeline("automatic-speech-recognition", model="openai/whisper-tiny")
-# VAD = VAD.from_hparams(source="speechbrain/vad-crdnn-libriparty", savedir="pretrained_models/vad-crdnn-libriparty")
 language_id = EncoderClassifier.from_hparams(source="speechbrain/lang-id-voxlingua107-ecapa")
 
 data = []
@@ -123,5 +120,6 @@ demo = gr.Interface(
     description="Speak into the microphone and see real-time audio processing results."
 )
 
-demo.launch()
 
+if __name__ == "__main__":
+    demo.launch()