Patent ID: 11966428
Assignee: MICROSOFT TECHNOLOGY LICENSING, LLC
Field: Computer technology (Electrical engineering)
Classification: CPC G | IPC G

Claim 0:
1. A computer-implemented method for generating a machine-trained model, comprising:
for a particular training example of linguistic information, obtaining a source item, a target item, a first auxiliary item, and a second auxiliary item,
the first and second auxiliary items conveying knowledge about the source item that is supplemental to any information conveyed by the source item itself, and the target item representing a transformed counterpart of the source item;
in a first processing path: forming a first instance of input information by combining the source item and the first auxiliary item; transforming the first instance of input information into first-path encoder output information using a first-path encoder; and transforming the first-path encoder output information into first-path decoder information using a first-path decoder;
in a second processing path: forming a second instance of input information by combing the source item and the target item; and transforming the second instance of input information into second-path encoder output information using a second-path encoder;
in a third processing path: forming a third instance of input information by combining the source item and the second auxiliary item; and transforming the third instance of input information into third-path decoder output information using a third-path encoder and a third-path decoder; and
updating training weights based on loss information generated using the first processing path, the second processing path, and the third processing path,
the method being repeating for additional training examples in a training data set,
the machine-trained model that is produced by the method corresponding to a trained counterpart of the first-path encoder and the first-path decoder.