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    DATA DRIVEN NATURAL LANGUAGE EVENT DETECTION AND CLASSIFICATION
    3.
    发明申请
    DATA DRIVEN NATURAL LANGUAGE EVENT DETECTION AND CLASSIFICATION 审中-公开
    数据驱动的自然语言事件检测和分类

    公开(公告)号：WO2017213686A1

    公开(公告)日：2017-12-14

    申请号：PCT/US2016/061917

    申请日：2016-11-14

    Applicant: APPLE INC.

    Inventor： BELLEGARDA, Jerome, R. ,  MARTEL, Mathieu, Jean ,  CARLHIAN, Alexandre ,  VINEL, Antoine ,  DOLFING, Jannes, G. ,  REKIK, Sabrine ,  BERGET, Markus ,  ARRAS, Hafid

    IPC: G10L15/00

    Abstract: Systems and processes for operating a digital assistant are provided. In accordance with one or more examples, a method includes, at a user device with one or more processors and memory, receiving unstructured natural language information from at least one user. The method also includes, in response to receiving the unstructured natural language information, determining whether event information is present in the unstructured natural language information. The method further includes, in accordance with a determination that event information is present within the unstructured natural language information, determining whether an agreement on an event is present in the unstructured natural language information. The method further includes, in accordance with a determination that an agreement on an event is present, determining an event type of the event and providing an event description based on the event type.

    Abstract translation: 提供了用于操作数字助理的系统和过程。 根据一个或多个示例，一种方法包括在具有一个或多个处理器和存储器的用户设备处从至少一个用户接收非结构化自然语言信息。 该方法还包括，响应于接收到非结构化自然语言信息，确定事件信息是否存在于非结构化自然语言信息中。 该方法还包括：根据事件信息存在于非结构化自然语言信息内的确定，确定关于事件的协议是否存在于非结构化自然语言信息中。 该方法进一步包括根据关于事件的约定存在的确定，确定事件的事件类型并且基于事件类型提供事件描述。

    LANGUAGE IDENTIFICATION USING N-GRAMS
    6.
    发明申请
    LANGUAGE IDENTIFICATION USING N-GRAMS 审中-公开
    使用N-GRAMS的语言识别

    公开(公告)号：WO2016195739A1

    公开(公告)日：2016-12-08

    申请号：PCT/US2015/053365

    申请日：2015-09-30

    Applicant: APPLE INC.

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

    IPC: G06F17/27 ,  G10L15/00

    CPC classification number: G06F17/275 ,  G06F17/2785 ,  G06F17/289 ,  G10L15/26

    Abstract: Systems and processes for language identification are provided. In accordance with one example, a method includes, at a first electronic device with one or more processors and memory, receiving user input including an n-gram and determining a similarity between a representation of the n-gram and a representation of a first language. The representation of the first language is based on an occurrence of each of a plurality of n-grams in the first language and an occurrence of each of the plurality of n-grams in a second language. The method further includes determining whether the similarity between the representation of the n-gram and the representation of the first language satisfies a threshold.

    Abstract translation: 提供用于语言识别的系统和过程。 根据一个示例，一种方法包括在具有一个或多个处理器和存储器的第一电子设备处接收包括n-gram的用户输入并且确定n-gram的表示和第一语言的表示之间的相似性 。 第一语言的表示基于第一语言中的多个n-gram中的每一个的出现以及以第二语言出现的多个n-gram中的每一个。 该方法还包括确定n-gram的表示与第一语言的表示之间的相似性是否满足阈值。

    SYSTEMS AND METHODS FOR STRUCTURED STEM AND SUFFIX LANGUAGE MODELS
    7.
    发明申请
    SYSTEMS AND METHODS FOR STRUCTURED STEM AND SUFFIX LANGUAGE MODELS 审中-公开
    结构化和语言模型的系统和方法

    公开(公告)号：WO2016149688A1

    公开(公告)日：2016-09-22

    申请号：PCT/US2016/023312

    申请日：2016-03-18

    Applicant: APPLE INC.

    Inventor： BELLEGARDA, Jerome, R. ,  YAMAN, Sibel

    IPC: G06F17/27

    CPC classification number: G10L15/063 ,  G06F3/023 ,  G06F17/276 ,  G10L15/197

    Abstract: Systems and methods are disclosed for predicting words using a structured stem and suffix n -gram language model. The systems and methods include determining, using a first n -gram word language model, a first probability of a stem based on a first portion of a previously-input word in the received input. Using a second n -gram language model, a second probability of a first suffix may be determined based at least on a second portion the previously-input word in the received input. Further, a third probability of a second suffix different from the first suffix may be determined using a third n -gram language model based at least on a third portion of the previously-input word in the received input. A fourth probability of a predicted word may be determined based on the first, second and third probabilities. One or more predicted words may be determined and provided as an output to the user.

    Abstract translation: 公开了用于使用结构化词干和后缀n-gram语言模型预测单词的系统和方法。 系统和方法包括基于接收的输入中的先前输入的单词的第一部分来确定使用第一n-gram语言模型的词干的第一概率。 使用第二n-gram语言模型，可以至少基于第二部分来确定接收到的输入中的先前输入的单词的第一后缀的第二概率。 此外，可以使用至少基于接收到的输入中的先前输入的单词的第三部分的第三n语言模型来确定与第一后缀不同的第二后缀的第三概率。 可以基于第一，第二和第三概率来确定预测字的第四概率。 可以确定一个或多个预测单词并将其提供给用户的输出。

    MULTILINGUAL WORD PREDICTION
    8.
    发明申请
    MULTILINGUAL WORD PREDICTION 审中-公开
    多语言词汇预测

    公开(公告)号：WO2017212306A1

    公开(公告)日：2017-12-14

    申请号：PCT/IB2016/001466

    申请日：2016-09-23

    Applicant: APPLE INC.

    Inventor： PAGALLO, Giulia ,  BELLEGARDA, Jerome, R. ,  RANGARAJAN SRIDHAR, Vivek, Kumar ,  MARSDEN, Randal

    IPC: G06F17/28

    Abstract: Systems and processes for multilingual word prediction are provided. In accordance with one example, a method includes, at an electronic device having one or more processors and memory, identifying context information of the electronic device and generating, with the one or more processors, a plurality of candidate words based on the context information, wherein a first candidate word of the plurality of candidate words corresponds to a first language of a plurality of languages and a second candidate word of the plurality of candidate words corresponds to a second language of the plurality of languages different than the first language.

    Abstract translation: 提供了用于多语言词语预测的系统和过程。 根据一个示例，一种方法包括：在具有一个或多个处理器和存储器的电子设备处，识别电子设备的上下文信息并且基于该上下文信息利用一个或多个处理器生成多个候选词， 其中，所述多个候选词中的第一候选词与多种语言中的第一语言相对应，并且所述多个候选词中的第二候选词与不同于所述第一语言的所述多种语言中的第二语言相对应。 p>

    MULTI-COMMAND SINGLE UTTERANCE INPUT METHOD
    9.
    发明申请
    MULTI-COMMAND SINGLE UTTERANCE INPUT METHOD 审中-公开
    多命令单输入法

    公开(公告)号：WO2015184186A1

    公开(公告)日：2015-12-03

    申请号：PCT/US2015/033051

    申请日：2015-05-28

    Applicant: APPLE INC.

    Inventor： GRUBER, Thomas, R. ,  SADDLER, Harry, J. ,  BELLEGARDA, Jerome, R. ,  NYEGGEN, Bryce, H. ,  SABATELLI, Alessandro

    IPC: G10L15/18 ,  G10L15/26 ,  G10L15/28 ,  G10L15/08 ,  G10L15/22

    CPC classification number: G10L15/1822 ,  G06F17/2705 ,  G10L15/1815 ,  G10L15/26 ,  G10L15/28 ,  G10L2015/088 ,  G10L2015/221 ,  G10L2015/223 ,  G10L2015/225 ,  G10L2015/228

    Abstract: Systems and processes are disclosed for handling a multi-part voice command for a virtual assistant. Speech input can be received from a user that includes multiple actionable commands within a single utterance. A text string can be generated from the speech input using a speech transcription process. The text string can be parsed into multiple candidate substrings based on domain keywords, imperative verbs, predetermined substring lengths, or the like. For each candidate substring, a probability can be determined indicating whether the candidate substring corresponds to an actionable command. Such probabilities can be determined based on semantic coherence, similarity to user request templates, querying services to determine manageability, or the like. If the probabilities exceed a threshold, the user intent of each substring can be determined, processes associated with the user intents can be executed, and an acknowledgment can be provided to the user.

    Abstract translation: 公开了用于处理虚拟助理的多部分语音命令的系统和过程。 语音输入可以从包含单个话语中的多个可操作命令的用户接收。 可以使用语音转录过程从语音输入生成文本串。 文本字符串可以基于域关键字，命令动词，预定子字符长度等被解析成多个候选子字符串。 对于每个候选子串，可以确定指示候选子串是否对应于可动作命令的概率。 这样的概率可以基于语义一致性，与用户请求模板的相似性，查询服务以确定可管理性等来确定。 如果概率超过阈值，则可以确定每个子串的用户意图，可以执行与用户意图相关联的过程，并且可以向用户提供确认。

    CREDIT CARD AUTO-FILL
    10.
    发明申请
    CREDIT CARD AUTO-FILL 审中-公开
    信用卡自动填充

    公开(公告)号：WO2015183818A1

    公开(公告)日：2015-12-03

    申请号：PCT/US2015/032449

    申请日：2015-05-26

    Applicant: APPLE INC.

    Inventor： DIXON, Ryan, S. ,  MEIER, Ueli ,  GROETHE, Karl, M. ,  BELLEGARDA, Jerome, R. ,  PALLO, Giulia, M.

    IPC: G06K9/22 ,  G06K9/72

    CPC classification number: G06K9/186 ,  G06K9/2081 ,  G06K9/228 ,  G06K9/325 ,  G06K9/72

    Abstract: Differing embodiments of this disclosure may employ one or all of the several techniques described herein to perform credit card recognition using electronic devices with integrated cameras. According to some embodiments, the credit card recognition process may comprise: obtaining a first representation of a first image, wherein the first representation comprises a first plurality of pixels; identifying a first credit card region within the first representation; extracting a first plurality of sub-regions from within the identified first credit card region, wherein a first sub-region comprises a credit card number, wherein a second sub-region comprises an expiration date, and wherein a third sub-region comprises a card holder name; generating a predicted character sequence for the first, second, and third sub- regions; and validating the predicted character sequences for at least the first, second, and third sub-regions using various credit card- related heuristics, e.g., expected character sequence length, expected character sequence format, and checksums.

    Abstract translation: 本公开的不同实施例可以采用本文所描述的几种技术中的一种或全部，以使用具有集成照相机的电子设备执行信用卡识别。 根据一些实施例，信用卡识别过程可以包括：获得第一图像的第一表示，其中第一表示包括第一多个像素; 识别所述第一表示内的第一信用卡区域; 从所识别的第一信用卡区域内提取第一多个子区域，其中第一子区域包括信用卡号码，其中第二子区域包括到期日期，并且其中第三子区域包括卡 持有人名称; 生成第一，第二和第三子区域的预测字符序列; 以及使用各种信用卡相关启发式，例如预期字符序列长度，期望字符序列格式和校验和来验证至少第一，第二和第三子区域的预测字符序列。

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