Comments (1)
Hi,
- I recall using 4 Nvidia Titan V GPUs.
- You can reduce the size of mini-batch, however, it would take a lot of time to train VoxCeleb2 using a single GPU
(regardless of your GPU generation, normally many recent systems take days using 4 GPUs )
My quick advice is to train the model using the train data of VoxCeleb1 and evaluate using VoxCeleb1 testset.
from rawnet.
Related Issues (20)
- About the pretrained model HOT 2
- script generate embedding HOT 1
- The generalization abality HOT 1
- How make embedding for single wave file? HOT 3
- The speaker embedding for the VoxCeleb1 was deleted HOT 1
- can you share code to load the pretrained model? HOT 1
- Unable to train RawNet1 using Keras HOT 1
- trained model for RawNet2_modified and RawNet2 HOT 4
- Weights of RawNet2_modified trained on VoxCeleb2 HOT 3
- Misbehaving losses while training RawNet1 HOT 2
- Too long IO time HOT 2
- The link for Pre-trained weight parameters for Rawnet 3 is not available. HOT 2
- Overfitting on VoxCeleb HOT 2
- Error in PreEmphasis Class HOT 2
- how to evaluate your implementation with a different dataset HOT 1
- Can I feed the 22050 sr wav to the pre-trained rawnet3 model ? HOT 3
- how to create the test_list for a new test dataset HOT 3
- how to use it for speaker verification HOT 6
- centre loss HOT 1
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from rawnet.