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How to train SEA model #4
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Do you mean SEA? You refer to the SEA paper for training details. |
I seem to have fallen into a mistake. Actually , in preparing data , the Encoder part of SEA model just be used. But I'm not sure that changing the speaker will make a difference. |
Does it matter if I take my own data and extract the features from the SEA model of 82 speakers that you pre-trained |
Yeah, sorry for spelling mistake |
The performance might degrade, but feel free to try. |
So the right thing to do is to train an SEA model with my own data and then extract the features. Could the sea part training code be provided? |
The majority of the code for SEA is here. You just need a data loader and an optimizer. |
Yes |
@auspicious3000 what is |
It is the one-hot speaker embedding. |
Hi! Could you point me to the SEA paper? I want to make sure I am reading the right one |
Self-Expressing Autoencoders for Unsupervised Spoken Term Discovery |
@auspicious3000 mask_sp_real = ~sequence_mask(len_real, cep_real0.size(1))# cep_real0 is MFCC that do not cut by [:, 0:20] |
The pretrained model sea.ckpt just fit dataset which have 82 speaker, However, I have a huge dataset including 300 speaker at least. How could I train a corresponding SAE model?
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