Diarization Inference Parameters
Hey guys,

I'm using "Speaker_Diarization_Inference.ipynb", I'm having a problem with Vad Diarization parameters
```
output_dir = os.path.join(ROOT,'outputs')
config.diarizer.paths2audio_files = paths2audio_files
config.diarizer.path2groundtruth_rttm_files = path2groundtruth_rttm_files
config.diarizer.out_dir = output_dir # Directory to store intermediate files and prediction outputs
config.diarizer.speaker_embeddings.model_path = pretrained_speaker_model

#Here we use our inhouse pretrained NeMo VAD 
config.diarizer.vad.model_path = pretrained_vad
config.diarizer.vad.window_length_in_sec = 0.15
config.diarizer.vad.shift_length_in_sec = 0.01
# config.diarizer.vad.threshold = 0.8 threshold would be deprecated in release 1.5
config.diarizer.vad.postprocessing_params.onset = 0.8 
config.diarizer.vad.postprocessing_params.offset = 0.7
config.diarizer.vad.postprocessing_params.min_duration_on = 0.1
config.diarizer.vad.postprocessing_params.min_duration_off = 0.3
```
Testing with different audios, I have to constantly change the parameters to get a better result with each audio, or avoid the error
`IndexError: list index out of range`

This happens to me mainly in version 1.4.0 of Nemo, in version 1.5.0 I noticed an improvement but still occurs the cases.

I'm not using the "vad_marblenet" model because it wasn't meeting my needs, I'm using a model that I'm training with "Voice_Activity_Detection.ipynb"

My question is if there is any metric for setting the values ​​of these parameters?
If you have an ideal value for these parameters, which has better results with a greater number of audios that go through the script?