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    Active learning for spoken language understanding
    51.
    发明授权
    Active learning for spoken language understanding 失效
    积极学习口语理解

    公开(公告)号：US07742918B1

    公开(公告)日：2010-06-22

    申请号：US11773681

    申请日：2007-07-05

    申请人： Dilek Z. Hakkani-Tur ,  Robert Elias Schapire ,  Gokhan Tur

    发明人： Dilek Z. Hakkani-Tur ,  Robert Elias Schapire ,  Gokhan Tur

    IPC分类号： G10L15/06

    CPC分类号： G10L15/063

    摘要： Disclosed is a system and method of training a spoken language understanding module. Such a module may be utilized in a spoken dialog system. The method of training a spoken language understanding module comprises training acoustic and language models using a small set of transcribed data St, recognizing utterances in a set Su that are candidates for transcription using the acoustic and language models, computing confidence scores of the utterances, selecting k utterances that have the smallest confidence scores from Su and transcribing them into a new set Si, redefining St as the union of St and Si, redefining Su as Su minus Si, and returning to the step of training acoustic and language models if word accuracy has not converged.

    摘要翻译： 公开了一种训练口语理解模块的系统和方法。 这样的模块可以在口语对话系统中使用。 训练口语理解模块的方法包括使用一小组转录数据St来训练声学和语言模型，使用声学和语言模型识别作为用于转录的候选者的集合Su中的话语，计算话语的置信度分数，选择 从苏的信心得分最小的k k and and Si Si Si Si Si，，ining ining of Si Si Si Si Si Si accuracy accuracy accuracy as as accuracy accuracy accuracy accuracy accuracy accuracy accuracy accuracy accuracy accuracy accuracy accuracy accuracy accuracy accuracy accuracy accuracy accuracy accuracy accuracy accuracy 没有收敛。

    Active learning for spoken language understanding
    52.
    发明授权
    Active learning for spoken language understanding 有权
    积极学习口语理解

    公开(公告)号：US07263486B1

    公开(公告)日：2007-08-28

    申请号：US10404699

    申请日：2003-04-01

    申请人： Dilek Z. Hakkani-Tur ,  Robert Elias Schapire ,  Gokhan Tur

    发明人： Dilek Z. Hakkani-Tur ,  Robert Elias Schapire ,  Gokhan Tur

    IPC分类号： G10L15/16

    CPC分类号： G10L15/063

    摘要： Disclosed is a system and method of training a spoken language understanding module. Such a module may be utilized in a spoken dialog system. The method of training a spoken language understanding module comprises training acoustic and language models using a small set of transcribed data ST, recognizing utterances in a set Su that are candidates for transcription using the acoustic and language models, computing confidence scores of the utterances, selecting k utterances that have the smallest confidence scores from Su and transcribing them into a new set Si, redefining St as the union of St and Si, redefining Su as Su minus Si, and returning to the step of training acoustic and language models if word accuracy has not converged.

    摘要翻译： 公开了一种训练口语理解模块的系统和方法。 这样的模块可以在口语对话系统中使用。 训练口语理解模块的方法包括使用一小组转录数据S IN来训练声学和语言模型，识别作为候选语言的候选语言的集合S < 使用声学和语言模型进行转录，计算话语的置信度分数，从S＆lt; U＆gt;中选择具有最小置信度分数的k个话语，并将它们转录成新的集合S < ，重新定义为S＆lt; t＆gt;和S＆lt; i＆lt; i＆lt; i＆gt;的并集，将S 重新定义为S＆lt; 如果字精度没有收敛，则返回到训练声学和语言模型的步骤。

    Apparatus and method for model adaptation for spoken language understanding
    57.
    发明授权
    Apparatus and method for model adaptation for spoken language understanding 有权
    用于口语理解的模型适应的装置和方法

    公开(公告)号：US07996219B2

    公开(公告)日：2011-08-09

    申请号：US11085587

    申请日：2005-03-21

    申请人： Gokhan Tur

    发明人： Gokhan Tur

    IPC分类号： G10L15/06

    CPC分类号： G10L15/065

    摘要： An apparatus and a method are provided for building a spoken language understanding model. Labeled data may be obtained for a target application. A new classification model may be formed for use with the target application by using the labeled data for adaptation of an existing classification model. In some implementations, the existing classification model may be used to determine the most informative examples to label.

    摘要翻译： 提供了一种用于构建口语理解模型的装置和方法。 可以为目标应用获得标签数据。 可以通过使用用于适应现有分类模型的标记数据来形成用于目标应用的新分类模型。 在一些实施方式中，现有的分类模型可用于确定最具信息性的标签示例。

    Method for building a natural language understanding model for a spoken dialog system
    58.
    发明授权
    Method for building a natural language understanding model for a spoken dialog system 有权
    建立语言对话系统的自然语言理解模型的方法

    公开(公告)号：US07933766B2

    公开(公告)日：2011-04-26

    申请号：US12582062

    申请日：2009-10-20

    申请人： Narendra K. Gupta ,  Mazin G. Rahim ,  Gokhan Tur ,  Antony Van der Mude

    发明人： Narendra K. Gupta ,  Mazin G. Rahim ,  Gokhan Tur ,  Antony Van der Mude

    IPC分类号： G06F17/27

    CPC分类号： G10L15/193 ,  G10L15/063 ,  G10L15/183

    摘要： A method of generating a natural language model for use in a spoken dialog system is disclosed. The method comprises using sample utterances and creating a number of hand crafted rules for each call-type defined in a labeling guide. A first NLU model is generated and tested using the hand crafted rules and sample utterances. A second NLU model is built using the sample utterances as new training data and using the hand crafted rules. The second NLU model is tested for performance using a first batch of labeled data. A series of NLU models are built by adding a previous batch of labeled data to training data and using a new batch of labeling data as test data to generate the series of NLU models with training data that increases constantly. If not all the labeling data is received, the method comprises repeating the step of building a series of NLU models until all labeling data is received. After all the training data is received, at least once, the method comprises building a third NLU model using all the labeling data, wherein the third NLU model is used in generating the spoken dialog service.

    摘要翻译： 公开了一种生成在口头对话系统中使用的自然语言模型的方法。 该方法包括对标签指南中定义的每个呼叫类型使用样本话语和创建许多手工制作规则。 使用手工制作的规则和样品说话来生成和测试第一个NLU模型。 使用示例语句作为新的训练数据并使用手工制作规则构建了第二个NLU模型。 使用第一批标签数据对第二个NLU模型进行性能测试。 通过将前一批标签数据添加到训练数据并使用新批签名数据作为测试数据来生成一系列NLU模型，训练数据不断增加，构建了一系列NLU模型。 如果不是全部接收到标签数据，则该方法包括重复建立一系列NLU模型的步骤，直到接收到所有标记数据为止。 在接收到所有训练数据之后，至少一次，该方法包括使用所有标签数据构建第三NLU模型，其中第三NLU模型用于生成口语对话服务。