Patent ID: 11869485
Assignee: TENCENT TECHNOLOGY (SHENZHEN) COMPANY LIMITED
Field: Computer technology (Electrical engineering)
Classification: CPC G | IPC G

Claim 6:
7. The method according to claim 1, the first encoding model and the first decoding model are trained by:
inputting at least two natural training sentences in a corpus into a training model, and training a classification capability of a second encoding model by using the training model to obtain the first encoding model, each natural training sentence corresponding to a language style, and the classification capability being classifying the input natural training sentence into a corresponding content vector and style vector;
obtaining at least one style vector outputted by the first encoding model when the first encoding model is obtained by training, each style vector being obtained by classifying the natural training sentence of a corresponding language style by the first encoding model; and
training a restoration capability of a second decoding model by the training model to obtain the first decoding model when the at least two natural training sentences are inputted into the training model, wherein:
the restoration capability is restoring into the natural training sentence according to the content vector and the style vector, and
the content vector indicates a meaning of the natural training sentence, and the style vector indicates a language style of the natural training sentence.