Patent ID: 11887008
Assignee: NEC CORPORATION
Field: Computer technology (Electrical engineering)
Classification: CPC G | IPC G

Claim 0:
1. A computer-implemented method for disentangled data generation, comprising:
accessing a dataset including a plurality of pairs, each formed from a given one of a plurality of input text structures and a given one of a plurality of style labels for the plurality of input text structures;
training an encoder neural network to disentangle a sequential text input into disentangled representations, including a content embedding and a style embedding, based on a subset of the dataset, using an objective function that includes a regularization term that minimizes mutual information between the content embedding and the style embedding, wherein the objective function is:

VAE+λreg, wherein λ is a hyperparameter reweighting a regularization reg and a variational autoencoder objective VAE, where reg is expressed as Dis+MI(s; c), including a disentanglement loss Dis and a mutual information term MI(s; c) based on a style embedding s and a content embedding c; and
training a generator neural network to generate a text output that includes content from the style embedding, expressed in a style other than that represented by the style embedding of the text input.