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    INTEGRATED WORD N-GRAM AND CLASS M-GRAM LANGUAGE MODELS
    32.
    发明申请
    INTEGRATED WORD N-GRAM AND CLASS M-GRAM LANGUAGE MODELS 有权
    综合词N-GRAM和类别M-GRAM语言模型

    公开(公告)号：US20160092434A1

    公开(公告)日：2016-03-31

    申请号：US14503370

    申请日：2014-09-30

    Applicant: Apple Inc.

    Inventor： Jerome R. BELLEGARDA

    IPC: G06F17/27 ,  G06F17/28

    CPC classification number: G06F17/279 ,  G06F17/2715 ,  G06F17/289

    Abstract: Systems and processes for discourse input processing are provided. In one example process, a discourse input can be received from a user. An integrated probability of a candidate word in the discourse input and one or more subclasses associated with the candidate word can be determined based on a conditional probability of the candidate word given one or more words in the discourse input, a probability of the candidate word within a corpus, and a conditional probability of the candidate word given one or more classes associated with the one or more words. A text string corresponding to the discourse input can be determined based on the integrated probability. An output based on the text string can be generated.

    Abstract translation: 提供了语篇输入处理的系统和过程。 在一个示例过程中，可以从用户接收话语输入。 可以基于在话语输入中给出一个或多个词的候选词的条件概率来确定话语输入中的候选词和与候选词相关联的一个或多个子类的综合概率，候选词的候选词的概率在 语料库，以及候选词给出与一个或多个单词相关联的一个或多个类别的条件概率。 可以基于综合概率来确定对应于话语输入的文本串。 可以生成基于文本字符串的输出。

    ENTROPY-GUIDED TEXT PREDICTION USING COMBINED WORD AND CHARACTER N-GRAM LANGUAGE MODELS
    33.
    发明申请
    ENTROPY-GUIDED TEXT PREDICTION USING COMBINED WORD AND CHARACTER N-GRAM LANGUAGE MODELS 审中-公开
    使用组合字和特征N-GRAM语言模型进行引导文本预测

    公开(公告)号：US20150347381A1

    公开(公告)日：2015-12-03

    申请号：US14713420

    申请日：2015-05-15

    Applicant: Apple Inc.

    Inventor： Jerome R. BELLEGARDA

    IPC: G06F17/27

    CPC classification number: G06F17/276

    Abstract: Systems and processes are disclosed for predicting words in a text entry environment. Candidate words and probabilities associated therewith can be determined by combining a word n-gram language model and a character m-gram language model. Based on entered text, candidate word probabilities from the word n-gram language model can be integrated with the corresponding candidate character probabilities from the character m-gram language model. A reduction in entropy can be determined from integrated candidate word probabilities before entry of the most recent character to integrated candidate word probabilities after entry of the most recent character. If the reduction in entropy exceeds a predetermined threshold, candidate words with high integrated probabilities can be displayed or otherwise made available to the user for selection. Otherwise, displaying candidate words can be deferred (e.g., pending receipt of an additional character from the user leading to reduced entropy in the candidate set).

    Abstract translation: 公开了用于在文本输入环境中预测单词的系统和过程。 可以通过组合单词n-gram语言模型和字符语法模型来确定与之相关联的候选词和概率。 基于输入的文本，从单词语言模型的候选词概率可以从字符模型语言模型中与相应的候选字符概率相结合。 可以在最近的字符输入之前的综合候选词概率到输入最新字符之后的综合候选词概率来确定熵的减少。 如果熵的减小超过预定阈值，则可以显示或以其他方式使用具有高集成概率的候选词供用户选择。 否则，可以延迟显示候选词（例如，等待从用户接收到额外的字符，导致候选集合中的熵减少）。

    UNIFIED RANKING WITH ENTROPY-WEIGHTED INFORMATION FOR PHRASE-BASED SEMANTIC AUTO-COMPLETION
    34.
    发明申请
    UNIFIED RANKING WITH ENTROPY-WEIGHTED INFORMATION FOR PHRASE-BASED SEMANTIC AUTO-COMPLETION 有权
    具有熵加权信息的基于PHRASE的语义自动完成的统一排名

    公开(公告)号：US20140365880A1

    公开(公告)日：2014-12-11

    申请号：US14298720

    申请日：2014-06-06

    Applicant: Apple Inc.

    Inventor： Jerome R. BELLEGARDA

    IPC: G06F17/30 ,  G06F17/27

    CPC classification number: G06F17/3097 ,  G06F17/2735 ,  G06F17/274 ,  G06F17/276 ,  G06F17/2785 ,  G06F17/2795 ,  G06F17/3053

    Abstract: Methods, systems, and computer-readable media related to a technique for combining two or more aspects of predictive information for auto-completion of user input, in particular, user commands directed to an intelligent digital assistant. Specifically, predictive information based on (1) usage frequency, (2) usage recency, and (3) semantic information encapsulated in an ontology (e.g., a network of domains) implemented by the digital assistant, are integrated in a balanced and sensible way within a unified framework, such that a consistent ranking of all completion candidates across all domains may be achieved. Auto-completions are selected and presented based on the unified ranking of all completion candidates.

    Abstract translation: 与用于组合用于自动完成用户输入的预测信息的两个或多个方面的技术相关的方法，系统和计算机可读介质，特别是指向智能数字助理的用户命令。 具体而言，以数字助理实现的（1）使用频率，（2）使用新近度和（3）封装在本体（例如，域的网络）中的语义信息的预测信息以平衡和合理的方式被整合 在统一的框架内，可以实现所有领域的所有完成候选人的一致排名。 基于所有完成候选人的统一排名选择和呈现自动完成。

    INTEGRATING STROKE-DISTRIBUTION INFORMATION INTO SPATIAL FEATURE EXTRACTION FOR AUTOMATIC HANDWRITING RECOGNITION
    35.
    发明申请
    INTEGRATING STROKE-DISTRIBUTION INFORMATION INTO SPATIAL FEATURE EXTRACTION FOR AUTOMATIC HANDWRITING RECOGNITION 审中-公开
    将分布式信息集成到空间特征提取中，用于自动手写识别

    公开(公告)号：US20140363082A1

    公开(公告)日：2014-12-11

    申请号：US14291722

    申请日：2014-05-30

    Applicant: Apple Inc.

    Inventor： Ryan S. DIXON ,  Jannes G. DOLFING ,  Ueli MEIER ,  Jerome R. BELLEGARDA

    IPC: G06K9/66 ,  G06K9/18

    CPC classification number: G06K9/00409 ,  G06K9/00402

    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. In some embodiments, temporally-derived features are used to improve recognition accuracy without compromising the stroke-order and stroke-direction independence of the recognition system.

    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。 手写输入模块提供实时，笔顺和笔画方向独立的手写识别。 在一些实施例中，使用时间推导的特征来提高识别精度，而不损害识别系统的笔画顺序和笔划方向独立性。

    VARIABLE LENGTH PHRASE PREDICTIONS
    36.
    发明公开
    VARIABLE LENGTH PHRASE PREDICTIONS 审中-公开

    公开(公告)号：US20230376690A1

    公开(公告)日：2023-11-23

    申请号：US17891088

    申请日：2022-08-18

    Applicant: Apple Inc.

    Inventor： Jerome R. BELLEGARDA ,  Bishal BARMAN ,  Hala ALMAGHOUT

    IPC: G06F40/289 ,  G06N3/04

    CPC classification number: G06F40/289 ,  G06N3/0454

    Abstract: Systems and processes for operating an intelligent automated assistant are provided. An example process includes, receiving a text and a set of contextual information associated with the text; determining, using a system of neural networks, a plurality of text predictions based on the text and the contextual information, wherein a first text prediction of the plurality of text predictions includes a word and a second text prediction of the plurality of text predictions includes a phrase and wherein the system of neural networks includes a first neural network for extracting a context, a second neural network for determining text predictions, and a third neural network for determining whether the text predictions are relevant to the context; and in accordance with a determination that a plurality of confidence scores associated with the plurality of text predictions exceed a predetermined threshold, providing the plurality of text predictions.

    SANITIZING WORD PREDICTIONS
    38.
    发明申请
    SANITIZING WORD PREDICTIONS 有权

    公开(公告)号：US20210149996A1

    公开(公告)日：2021-05-20

    申请号：US16689831

    申请日：2019-11-20

    Applicant: Apple Inc.

    Inventor： Jerome R. BELLEGARDA

    IPC: G06F17/27 ,  G10L15/22 ,  G06F3/16 ,  G10L15/26 ,  G06F3/023 ,  G10L15/18

    Abstract: Systems and processes for modifying word predictions are provided. In one example, a user input is received including one or more words. A prediction of a word sequence corresponding to one or more words is obtained, and context information associated with the word sequence is obtained. In accordance with a determination, based on the context information, that the prediction of the word sequence corresponds to a predetermined semantic reference, the prediction of the word sequence is modified, and an output is provided corresponding to the modified prediction of the word sequence. In accordance with a determination, based on the context information, that the prediction of the word sequence does not correspond to a predetermined semantic reference, an output is provided corresponding to the prediction of the word sequence.

    GLOBAL SEMANTIC WORD EMBEDDINGS USING BI-DIRECTIONAL RECURRENT NEURAL NETWORKS
    39.
    发明申请
    GLOBAL SEMANTIC WORD EMBEDDINGS USING BI-DIRECTIONAL RECURRENT NEURAL NETWORKS 审中-公开

    公开(公告)号：US20190355346A1

    公开(公告)日：2019-11-21

    申请号：US16111055

    申请日：2018-08-23

    Applicant: Apple Inc.

    Inventor： Jerome R. BELLEGARDA

    IPC: G10L15/06 ,  G10L15/18 ,  G10L15/16 ,  G10L15/30 ,  G06N3/08

    Abstract: Systems and processes for operating a digital assistant are provided. In accordance with one or more examples, a method includes, receiving training data for a data-driven learning network. The training data include a plurality of word sequences. The method further includes obtaining representations of an initial set of semantic categories associated with the words included in the training data; and training the data-driven learning network based on the plurality of word sequences included in the training data and based on the representations of the initial set of semantic categories. The training is performed using the word sequences in their entirety. The method further includes obtaining, based on the trained data-driven learning network, representations of a set of semantic embeddings of the words included in the training data; and providing the representations of the set of semantic embeddings to at least one of a plurality of different natural language processing tasks.

    MULTI-TASK RECURRENT NEURAL NETWORK ARCHITECTURE FOR EFFICIENT MORPHOLOGY HANDLING IN NEURAL LANGUAGE MODELING
    40.
    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.

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