Speaker Verification
Hi,

I'm working with NeMo to find out if a particular voice belongs to a specific person, to use as authentication. I saw several issues about and tested some scripts but I don't know if I'm on the right path.
From what I've read, the best script to follow would be this https://github.com/NVIDIA/NeMo/blob/main/examples/speaker_recognition/voxceleb_eval.py where a score is calculated on two audio embeddings and on this score I could define if both are the same person.
For simplicity's sake leave it that way where I easily retrieve the embeddings of two audios and do the calculation:

```
verification_model = nemo_asr.models.EncDecSpeakerLabelModel.from_pretrained(model_name="speakerverification_speakernet")
emb = verification_model.get_embedding('Person1.wav').cpu()[0]
emb2 = verification_model.get_embedding('Person2.wav').cpu()[0]
score = np.dot(emb, emb2) / ((np.dot(emb, emb) * np.dot(emb2, emb2)) ** 0.5)
score = (score + 1) / 2
```

When testing this script I realized that people of the same sex have a hard time getting it right... I have this doubt because the script seems too "simple" for a very complicated task that involves this voice analysis. This way what I'm doing is right? Or should I go the other way?