The implementation of "Cross-Reconstructed Emotion Disentanglement" module

[yChenN1]

Hi @jixinya,
Thanks for your excellent work!
I am curious about the implementation of Cross-Reconstructed Emotion Disentanglement. In the paper, you say, "Given four audio samples Xi,m, Xj,n, Xj,m, Xi,n" for disentangling. However, the implementation in this project is a little different: you sample 2 emotions and 3 contents and set X11, X21, X12, X23 as inputs, and X11, X11, X12, X12 as four targets to calculate the cross reconstruction loss and self reconstruction loss. (as below)

EVP/train/disentanglement/code/dataload.py

Lines 103 to 107 in 990ea8b

	return {"input11": mfcc11, "target11": target11,
	"target21": target11, "target22": target12,
	"input12": mfcc12, "target12": target12,
	"label1": label1, "label2": label2,
	"input21": mfcc21, "input32": mfcc32

Could you please explain this? Hope for your response.