PREDICTIVE CONVERSION OF LANGUAGE INPUT
    1.
    发明申请
    PREDICTIVE CONVERSION OF LANGUAGE INPUT 有权
    语言输入的预测转换

    公开(公告)号:US20150370780A1

    公开(公告)日:2015-12-24

    申请号:US14839830

    申请日:2015-08-28

    Applicant: Apple Inc.

    Abstract: Systems and processes for predictive conversion of language input are provided. In one example process, text composed by a user can be obtained. Input comprising a sequence of symbols of a first symbolic system can be received from the user. Candidate word strings corresponding to the sequence of symbols can be determined. Each candidate word string can comprise two or more words of a second symbolic system. The candidate word strings can be ranked based on a probability of occurrence of each candidate word string in the obtained text. Based on the ranking, a portion of the candidate word strings can be displayed for selection by the user.

    Abstract translation: 提供了语言输入预测转换的系统和过程。 在一个示例过程中,可以获得由用户组成的文本。 可以从用户接收包括第一符号系统的符号序列的输入。 可以确定与符号序列对应的候选字串。 每个候选字串可以包括第二符号系统的两个或更多个字。 候选词串可以基于获得的文本中每个候选词串的出现概率来排序。 基于排名,可以显示候选字串的一部分以供用户选择。

    ADVERSARIAL DISCRIMINATIVE NEURAL LANGUAGE MODEL ADAPTATION

    公开(公告)号:US20220229985A1

    公开(公告)日:2022-07-21

    申请号:US17340990

    申请日:2021-06-07

    Applicant: Apple Inc.

    Abstract: Systems and methods for updating a language model are provided. One example method includes, at an electronic device with one or more processors and memory, training a first language model using a training data set comprising user-generated and user-relevant data, and storing a reference version of the first language model including a first overall probability distribution. Based on the reference version of the first language model, a second language model including a second overall probability distribution is updated (i.e., adapted) using the first overall probability distribution as a constraint on the second overall probability distribution.

    ANALYSIS AND VALIDATION OF LANGUAGE MODELS

    公开(公告)号:US20220067283A1

    公开(公告)日:2022-03-03

    申请号:US17108933

    申请日:2020-12-01

    Applicant: Apple Inc.

    Abstract: Systems and methods for analysis and validation of language models trained using data that is unavailable or inaccessible are provided. One example method includes, at an electronic device with one or more processors and memory, obtaining a first set of data corresponding to one or more tokens predicted based on one or more previous tokens. The method determines a probability that the first set of data corresponds to a prediction generated by a first language model trained using a user privacy preserving training process. In accordance with a determination that the probability is within a predetermined range, the method determines that the one or more tokens correspond to a prediction associated with the user privacy preserving training process and outputs a predicted token sequence including the one or more tokens and the one or more previous tokens.

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