taoruijie / avcleanse Goto Github PK

Thanks for you open source code. In paper, I guess you train speaker and face embedding network respectively. Then, use it to clean the data. But in speaker-face folder, you train speaker and face embedding network together. I want to ask why you do this. Thank you.

Hello, Thanks for the code and your sharing. When I was doing evaluation for this code these days, the pretrain visual model including V-Vox2.model and V-Glint.model, in my experiment, do not have a correct parameter numbers of the visual model for both IResNet18 and IResNet 50, resulting in a terrible evaluation scores and EER.

Specifically, the parameter of V-Vox2.model is 422 while the model.state_dict() only have 188 parameters. Meanwhile, the parameter of V-Glint.model is missing face_loss.weights so numbers of parameter is one smaller. I wonder if I was doing wrong in the process of evaluation or the pretrained model given is not correct.

( by the way, the pretrained audio model given is correct and works well. )

Hello, I'm working on audio-visual speaker recognition system and I read your code.

I would like to ask if your cleasing code is included in this repo? Or that you only provided clean list for training data.

Cause I didn't find the part that you did cleasing steps. Does that means if your models in this repo are just simple speaker recognition models?

Thanks for your reply!

Hello, I wanna ask how to generate the corresponding face data through the voxceleb video dataset, because I haven't learned much about face recognition.