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    System and method for accessing and annotating electronic medical records using a multi-modal interface
    31.
    发明授权
    System and method for accessing and annotating electronic medical records using a multi-modal interface 有权
    使用多模式界面访问和注释电子病历的系统和方法

    公开(公告)号：US07499862B1

    公开(公告)日：2009-03-03

    申请号：US11788890

    申请日：2007-04-23

    申请人： Srinivas Bangalore ,  Charles Douglas Blewett ,  Michael Johnston

    发明人： Srinivas Bangalore ,  Charles Douglas Blewett ,  Michael Johnston

    IPC分类号： G10L21/00

    CPC分类号： G06F3/04883 ,  G06F3/038 ,  G06F3/167 ,  G06F19/00 ,  G10L15/26 ,  G16H10/60 ,  G16H15/00 ,  G16H40/63 ,  Y10S707/99945 ,  Y10S707/99948

    摘要： A system and method of exchanging medical information between a user and a computer device is disclosed. The computer device can receive user input in one of a plurality of types of user input comprising speech, pen, gesture and a combination of speech, pen and gesture. The method comprises receiving information from the user associated with a medical condition and a bodily location of the medical condition on a patient in one of a plurality of types of user input, presenting in one of a plurality of types of system output an indication of the received medical condition and the bodily location of the medical condition, and presenting to the user an indication that the computer device is ready to receive further information. The invention enables a more flexible multi-modal interactive environment for entering medical information into a computer device. The medical device also generates multi-modal output for presenting a patient's medical condition in an efficient manner.

    摘要翻译： 公开了一种在用户和计算机设备之间交换医疗信息的系统和方法。 计算机设备可以以包括语音，笔，手势以及语音，笔和手势的组合的多种类型的用户输入中的一种接收用户输入。 所述方法包括以多种类型的用户输入中的一种类型的用户输入中的与患者的医疗状况和医疗状况的身体位置相关联的信息，以多种类型的系统中的一种输出， 接收到医疗状况和医疗状况的身体位置，并向用户呈现计算机设备准备好接收更多信息的指示。 本发明实现了用于将医疗信息输入计算机设备的更灵活的多模态交互环境。 医疗装置还产生用于以有效的方式呈现患者的医疗状况的多模式输出。

    Discriminative training of models for sequence classification
    33.
    发明申请
    Discriminative training of models for sequence classification 审中-公开
    序列分类模型的辨别性训练

    公开(公告)号：US20080162117A1

    公开(公告)日：2008-07-03

    申请号：US11646983

    申请日：2006-12-28

    申请人： Srinivas Bangalore ,  Patrick Haffner ,  Stephan Kanthak

    发明人： Srinivas Bangalore ,  Patrick Haffner ,  Stephan Kanthak

    IPC分类号： G06F17/21

    CPC分类号： G06F17/2818

    摘要： Classification of sequences, such as the translation of natural language sentences, is carried out using an independence assumption. The independence assumption is an assumption that the probability of a correct translation of a source sentence word into a particular target sentence word is independent of the translation of other words in the sentence. Although this assumption is not a correct one, a high level of word translation accuracy is nonetheless achieved. In particular, discriminative training is used to develop models for each target vocabulary word based on a set of features of the corresponding source word in training sentences, with at least one of those features relating to the context of the source word. Each model comprises a weight vector for the corresponding target vocabulary word. The weights comprising the vectors are associated with respective ones of the features; each weight is a measure of the extent to which the presence of that feature for the source word makes it more probable that the target word in question is the correct one.

    摘要翻译： 使用独立假设进行序列分类，如自然语言句子的翻译。 独立性假设是将源语句正确翻译成特定目标句子词的概率与句子中其他单词的翻译无关的假设。 尽管这种假设不是正确的，但仍然会实现高水平的字翻译精度。 特别地，歧视性训练被用于基于训练句子中相应源词的一组特征来开发每个目标词汇词的模型，其中至少一个与源词的上下文有关的特征。 每个模型包括对应的目标词汇单词的权重向量。 包括向量的权重与相应的特征相关联; 每个权重是衡量源字符的该特征的存在程度使得所述目标词更可能是正确的。

    System and method for natural language generation
    34.
    发明授权
    System and method for natural language generation 有权
    自然语言生成的系统和方法

    公开(公告)号：US07231341B2

    公开(公告)日：2007-06-12

    申请号：US11195973

    申请日：2005-08-03

    申请人： Srinivas Bangalore ,  Owen Christopher Rambow

    发明人： Srinivas Bangalore ,  Owen Christopher Rambow

    IPC分类号： G06F17/20

    CPC分类号： G06F17/271 ,  G06F17/2881

    摘要： A system, method and computer-readable medium for generating natural language utilizes a stochastic process to choose a derivation tree according to a predetermined grammar, such as tree-adjoined grammar (TAG). A word lattice is created from a single semi-specified derivation tree and the proper path (i.e., desired output string) is selected from the lattice using a least cost, or other appropriate algorithms.

    摘要翻译： 用于生成自然语言的系统，方法和计算机可读介质利用随机过程根据诸如树相邻语法（TAG）的预定语法来选择导出树。 从单个半指定的导出树创建一个字格，并且使用最小成本或其他适当的算法从网格中选择适当的路径（即期望的输出串）。

    System and method for accessing and annotating electronic medical records using multi-modal interface
    35.
    发明授权
    System and method for accessing and annotating electronic medical records using multi-modal interface 有权
    使用多模态界面访问和注释电子病历的系统和方法

    公开(公告)号：US07225131B1

    公开(公告)日：2007-05-29

    申请号：US10329123

    申请日：2002-12-24

    申请人： Srinivas Bangalore ,  Charles Douglas Blewett ,  Michael Johnston

    发明人： Srinivas Bangalore ,  Charles Douglas Blewett ,  Michael Johnston

    IPC分类号： G10L21/00

    CPC分类号： G06F3/04883 ,  G06F3/038 ,  G06F3/167 ,  G06F19/00 ,  G10L15/26 ,  G16H10/60 ,  G16H15/00 ,  G16H40/63 ,  Y10S707/99945 ,  Y10S707/99948

    摘要： A system and method of exchanging medical information between a user and a computer device is disclosed. The computer device can receive user input in one of a plurality of types of user input comprising speech, pen, gesture and a combination of speech, pen and gesture. The method comprises receiving information from the user associated with a medical condition and a bodily location of the medical condition on a patient in one of a plurality of types of user input, presenting in one of a plurality of types of system output an indication of the received medical condition and the bodily location of the medical condition, and presenting to the user an indication that the computer device is ready to receive further information. The invention enables a more flexible multi-modal interactive environment for entering medical information into a computer device. The medical device also generates multi modal output for presenting a patient's medical condition in an efficient manner.

    摘要翻译： 公开了一种在用户和计算机设备之间交换医疗信息的系统和方法。 计算机设备可以以包括语音，笔，手势以及语音，笔和手势的组合的多种类型的用户输入中的一种接收用户输入。 所述方法包括以多种类型的用户输入中的一种类型的用户输入中的与患者的医疗状况和医疗状况的身体位置相关联的信息，以多种类型的系统中的一种输出， 接收到医疗状况和医疗状况的身体位置，并向用户呈现计算机设备准备好接收更多信息的指示。 本发明实现了用于将医疗信息输入计算机设备的更灵活的多模态交互环境。 该医疗装置还产生多模式输出，用于以有效的方式呈现患者的医疗状况。

    System and method for learning latent representations for natural language tasks
    37.
    发明授权
    System and method for learning latent representations for natural language tasks 有权
    学习自然语言任务的潜在表征的系统和方法

    公开(公告)号：US09135241B2

    公开(公告)日：2015-09-15

    申请号：US12963126

    申请日：2010-12-08

    申请人： Srinivas Bangalore ,  Sumit Chopra

    发明人： Srinivas Bangalore ,  Sumit Chopra

    IPC分类号： G06F17/28

    CPC分类号： G06F17/28

    摘要： Disclosed herein are systems, methods, and non-transitory computer-readable storage media for learning latent representations for natural language tasks. A system configured to practice the method analyzes, for a first natural language processing task, a first natural language corpus to generate a latent representation for words in the first corpus. Then the system analyzes, for a second natural language processing task, a second natural language corpus having a target word, and predicts a label for the target word based on the latent representation. In one variation, the target word is one or more word such as a rare word and/or a word not encountered in the first natural language corpus. The system can optionally assigning the label to the target word. The system can operate according to a connectionist model that includes a learnable linear mapping that maps each word in the first corpus to a low dimensional latent space.

    摘要翻译： 本文公开了用于学习自然语言任务的潜在表示的系统，方法和非暂时的计算机可读存储介质。 一种被配置为练习该方法的系统，分析第一自然语言处理任务中的第一自然语言语料库以产生第一语料库中的单词的潜在表示。 然后，系统针对第二自然语言处理任务分析具有目标词的第二自然语言语料库，并且基于潜在表示来预测目标词的标签。 在一个变体中，目标词是一个或多个单词，例如在第一自然语言语料库中不遇到的罕见单词和/或单词。 系统可以选择将标签分配给目标字。 该系统可以根据连接主义模型来操作，该连接主义模型包括将第一语料库中的每个单词映射到低维空间的可学习的线性映射。

    System and method of extracting clauses for spoken language understanding
    39.
    发明授权
    System and method of extracting clauses for spoken language understanding 有权
    提取语言理解条款的系统和方法

    公开(公告)号：US08818793B1

    公开(公告)日：2014-08-26

    申请号：US10446489

    申请日：2003-05-28

    申请人： Srinivas Bangalore ,  Narendra K. Gupta ,  Mazin G Rahim

    发明人： Srinivas Bangalore ,  Narendra K. Gupta ,  Mazin G Rahim

    IPC分类号： G06F17/27

    CPC分类号： G10L15/063 ,  G06F17/271 ,  G06F17/277 ,  G10L2015/0635

    摘要： A clausifier and method of extracting clauses for spoken language understanding are disclosed. The method relates to generating a set of clauses from speech utterance text and comprises inserting at least one boundary tag in speech utterance text related to sentence boundaries, inserting at least one edit tag indicating a portion of the speech utterance text to remove, and inserting at least one conjunction tag within the speech utterance text. The result is a set of clauses that may be identified within the speech utterance text according to the inserted at least one boundary tag, at least one edit tag and at least one conjunction tag. The disclosed clausifier comprises a sentence boundary classifier, an edit detector classifier, and a conjunction detector classifier. The clausifier may comprise a single classifier or a plurality of classifiers to perform the steps of identifying sentence boundaries, editing text, and identifying conjunctions within the text.

    摘要翻译： 公开了一种提取语言理解条款的分类器和方法。 该方法涉及从语音话语文本生成一组子句，并且包括在与句子边界相关的语音话语文本中插入至少一个边界标签，插入至少一个编辑标签，该编辑标签指示语音话语文本的一部分以去除并插入 讲话话语文本内的至少一个连接标签。 结果是可以根据插入的至少一个边界标签，至少一个编辑标签和至少一个连接标签在语音发音文本内识别的一组子句。 所公开的分类器包括句子边界分类器，编辑检测器分类器和连接检测器分类器。 克隆器可以包括单个分类器或多个分类器，以执行识别句子边界，编辑文本以及识别文本内的连词的步骤。