h3

app.py

@@ -8,7 +8,7 @@ from io import BytesIO
 
 # Create a dropdown to select the model
 model_options = ["base", "small", "medium", "large", "large-v2"]
-default_model = "medium"
+default_model = "base"
 model_name = st.selectbox("Select a model", options=model_options, index=model_options.index(default_model))
 
 # Load the selected model
@@ -25,7 +25,7 @@ if st.button('Transcribe'):
         # Resample the audio data if necessary
         expected_sample_rate = 16000  # replace with the sample rate expected by the model
         if sample_rate != expected_sample_rate:
-            audio_data = librosa.resample(audio_data, sample_rate, expected_sample_rate)
+            audio_data = librosa.resample(audio_data, orig_sr=sample_rate, target_sr=expected_sample_rate)
         # Convert the audio data to float
         audio_data = torch.from_numpy(audio_data).float()
         # Transcribe the audio file