Linguistic model training method and device as well as linguistic model construction method and device

Abstract

The embodiment of the invention discloses a linguistic model training method. The method comprises the steps that a terminal determines a first linguistic model; the terminal trains the first linguistic model through historical input data locally generated so that a trained first linguistic model can be obtained; and the terminal sends first model parameters of the trained first linguistic model to a server, wherein the first model parameters are used for determining second model parameters of a second linguistic model, and the second linguistic model is used for displaying candidate items obtained through association for the terminal. Therefore, in the process of obtaining the second linguistic model, the historical input data containing the privacy of a user are trained on the local terminal through the first linguistic model, the original historical input data do not need to be uploaded to the server, and thus the risk of exposure of the private information of the user is reduced; and meanwhile, the terminal only uploads the first model parameters of the trained first linguistic model to the server, thus the uploaded data volume is relatively small, and therefore, the uploadingefficiency of the terminal during the process of obtaining the second linguistic model is improved.

Description

technical field [0001] This application relates to the field of input methods, in particular to a language model training method, construction method and device. Background technique [0002] The user can input a character string through an input method, and select the input method to display the candidates on the screen according to the character string. In addition to displaying candidates according to the input string, the input method can also display corresponding candidates according to the content that the user has selected on the screen in some cases. [0003] The candidates displayed by the input method can be obtained through language model association, and the language model needs to be trained with a large amount of corpus to improve the association accuracy. [0004] In some possible implementations, the input method trains the language model on the network side through a large number of historical input data of users, and the acquired historical input data is ...

AI Technical Summary

Problems solved by technology

Either way will lead to the risk of exposure of the user's private information, such as the specific content entered by the user, making it difficult to protect the user's privacy in the process of training the language model

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