How to reproduce the same result as in the paper
I tried to reproduce the result of speakerrecognition_speakernet results which:

` description="SpeakerNet_recognition model trained end-to-end for speaker recognition purposes with cross_entropy loss. It was trained on voxceleb 1, voxceleb 2 dev datasets and augmented with musan music and noise. Speaker Recognition model achieves 2.65% EER on voxceleb-O cleaned trial file",`

So, to infer label we need two files:
1- train_manifest=/path/to/train/manifest/file'
2- test_manifest=/path/to/train/manifest/file'

and then call the provided script: `python speaker_reco_infer.py --spkr_model='/path/to/.nemo/file' --train_manifest=/path/to/train/manifest/file --test_manifest=/path/to/train/manifest/file --batch_size=32`

So, correct me please. The test_manifest is `https://www.robots.ox.ac.uk/~vgg/data/voxceleb/meta/veri_test2.txt`. But Usualy we need it in json format where can I find this file?

Where can I find the `train_manifest`?

If I am wrong, how can reproduce the speaker recognition on voxceleb1 and voxceleb2 as in the paper? Indeed, you was using Voxceleb1 and Voxceleb2 for training. Can for example, we use Voxceleb1 for training and then Voxceleb2 for testing? 