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    MULTI-TASK RECURRENT NEURAL NETWORK ARCHITECTURE FOR EFFICIENT MORPHOLOGY HANDLING IN NEURAL LANGUAGE MODELING
    12.
    发明申请
    MULTI-TASK RECURRENT NEURAL NETWORK ARCHITECTURE FOR EFFICIENT MORPHOLOGY HANDLING IN NEURAL LANGUAGE MODELING 审中-公开

    公开(公告)号：US20180349349A1

    公开(公告)日：2018-12-06

    申请号：US15851487

    申请日：2017-12-21

    Applicant: Apple Inc.

    Inventor： Jerome R. BELLEGARDA ,  Jannes G. DOLFING

    IPC: G06F17/27 ,  G10L25/30

    Abstract: The present disclosure generally relates to systems and processes for morpheme-based word prediction. An example method includes receiving a current word; determining a context of the current word based on the current word and a context of a previous word; determining, using a morpheme-based language model, a likelihood of a prefix based on the context of the current word; determining, using the morpheme-based language model, a likelihood of a stem based on the context of the current word; determining, using the morpheme-based language model, a likelihood of a suffix based on the context of the current word; determining a next word based on the likelihood of the prefix, the likelihood of the stem, and the likelihood of the suffix; and providing an output including the next word.

    UNIFIED FRAMEWORK FOR TEXT CONVERSION AND PREDICTION
    13.
    发明申请
    UNIFIED FRAMEWORK FOR TEXT CONVERSION AND PREDICTION 审中-公开

    公开(公告)号：US20180322112A1

    公开(公告)日：2018-11-08

    申请号：US15673587

    申请日：2017-08-10

    Applicant: Apple Inc.

    Inventor： Jerome R. BELLEGARDA ,  Jannes G. DOLFING ,  Xin WANG

    IPC: G06F17/27 ,  G06F17/28

    CPC classification number: G06F17/276 ,  G06F17/2217 ,  G06F17/2735 ,  G06F17/2818

    Abstract: The present disclosure generally relates to integrated text conversion and prediction. In an example process, a current character input of a first writing system is received. A first current character context in the first writing system is determined based on the current character input and a first previous character context in the first writing system. A second current character context in a second writing system is determined based on the first current character context, a second previous character context in the second writing system, and a character representation in the second writing system. A current word context in the second writing system is determined based on the second current character context, a previous word context in the second writing system, and a word representation in the second writing system. Based on the current word context, a probability distribution over a word inventory in the second writing system is determined.

    MANAGING REAL-TIME HANDWRITING RECOGNITION
    14.
    发明申请
    MANAGING REAL-TIME HANDWRITING RECOGNITION 审中-公开
    管理实时手写识别

    公开(公告)号：US20170010802A1

    公开(公告)日：2017-01-12

    申请号：US15275309

    申请日：2016-09-23

    Applicant: Apple Inc.

    Inventor： Mei-Qun XIA ,  Jannes G. DOLFING ,  Ryan S. DIXON ,  Karl M. GROETHE ,  Karan MISRA ,  Jerome R. BELLEGARDA ,  Ueli MEIER

    IPC: G06F3/0488 ,  G06F3/0482 ,  G06K9/00 ,  G06F17/24 ,  G06F17/27

    CPC classification number: G06F3/04883 ,  G06F3/018 ,  G06F3/0482 ,  G06F17/24 ,  G06F17/276 ,  G06K9/00416 ,  G06K9/00422 ,  G06K9/00436

    Abstract: Methods, systems, and computer-readable media related to a technique for providing handwriting input functionality on a user device. A handwriting recognition module is trained to have a repertoire comprising multiple non-overlapping scripts and capable of recognizing tens of thousands of characters using a single handwriting recognition model. The handwriting input module provides real-time, stroke-order and stroke-direction independent handwriting recognition for multi-character handwriting input. In particular, real-time, stroke-order and stroke-direction independent handwriting recognition is provided for multi-character, or sentence level Chinese handwriting recognition. User interfaces for providing the handwriting input functionality are also disclosed.

    Abstract translation: 与用于在用户设备上提供手写输入功能的技术相关的方法，系统和计算机可读介质。 训练手写识别模块以具有包括多个非重叠脚本的节目，并且能够使用单个手写识别模型识别成千上万个字符。 手写输入模块为多字符手写输入提供实时，笔顺和笔迹方向独立的手写识别。 特别地，为多字符或句子级中文手写识别提供实时，笔顺和笔画方向独立的手写识别。 还公开了用于提供手写输入功能的用户界面。

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