Spoken language understanding that incorporates prior knowledge into boosting
    1.
    发明授权
    Spoken language understanding that incorporates prior knowledge into boosting 有权
    将先前知识纳入提升的口语理解

    公开(公告)号:US07152029B2

    公开(公告)日:2006-12-19

    申请号:US10160461

    申请日:2002-05-31

    IPC分类号: G06F17/20

    CPC分类号: G10L15/063

    摘要: A system for understanding entries, such as speech, develops a classifier by employing prior knowledge with which a given corpus of training entries is enlarged threefold. A rule is created for each of the labels employed in the classifyier, and the created rules are applied to the given corpus to create a corpus of attachments by appending a weight of ηp(x), or 1−ηp(x), to labels of entries that meet, or fail to meet, respectively, conditions of the labels' rules, and to also create a corpus of non-attachments by appending a weight of 1−ηp(x), or ηp(x), to labels of entries that meet, or fail to meet conditions of the labels' rules.

    摘要翻译: 用于理解诸如言语之类的条目的系统通过采用将给定的训练条目语料库放大三倍的先验知识来开发分类器。 为分类器中使用的每个标签创建一个规则,并将创建的规则应用于给定的语料库以通过将etap(x)或1-etap(x)的权重附加到标签来创建附件语料库 分别符合或未能满足标签规则的条件的条目,并通过将1-etap(x)或etap(x)的权重附加到标签的标签上来创建非附件语料库 满足或不符合标签规则条件的条目。

    Spoken language understanding that incorporates prior knowledge into boosting
    2.
    发明授权
    Spoken language understanding that incorporates prior knowledge into boosting 有权
    将先前知识纳入提升的口语理解

    公开(公告)号:US07328146B1

    公开(公告)日:2008-02-05

    申请号:US11484120

    申请日:2006-07-11

    IPC分类号: G06F17/20

    CPC分类号: G06F17/28

    摘要: A system for understanding entries, such as speech, develops a classifier by employing prior knowledge with which a given corpus of training entries is enlarged threefold. A rule is created for each of the labels employed in the classifier, and the created rules are applied to the given corpus to create a corpus of attachments by appending a weight of ηp(x), or 1−ηp(x), to labels of entries that meet, or fail to meet, respectively, conditions of the labels' rules, and to also create a corpus of non-attachments by appending a weight of 1−ηp(x), or ηp(x), to labels of entries that meet, or fail to meet conditions of the labels' rules.

    摘要翻译: 用于理解诸如言语之类的条目的系统通过采用将给定的训练条目语料库放大三倍的先验知识来开发分类器。 为分类器中使用的每个标签创建规则,并将创建的规则应用于给定的语料库,以通过将一个权重为etap(x)或1-etap(x)附加到标签来创建附件语料库 分别符合或未能满足标签规则的条件的条目,并通过将1-etap(x)或etap(x)的权重附加到标签的标签上来创建非附件语料库 满足或不符合标签规则条件的条目。

    Method of generation a labeling guide for spoken dialog services
    4.
    发明授权
    Method of generation a labeling guide for spoken dialog services 有权
    生成口语对话服务标签指南的方法

    公开(公告)号:US07729902B1

    公开(公告)日:2010-06-01

    申请号:US11927738

    申请日:2007-10-30

    IPC分类号: G06F17/27 G06F17/21

    摘要: A method is disclosed for designing a labeling guide for use by a labeler in labeling data used for training a spoken language understanding (SLU) module for an application. The method comprises a labeling guide designer selecting domain-independent actions applicable to an application, selecting domain-dependent objects according to characteristics of the application, and generating a labeling guide using the selected domain-independent actions and selected domain-dependent objects. An advantage of the labeling guide generated in this manner is that the labeling guide designer can easily port the labeling guide to a new application by selecting a set of domain-independent action and then selecting the domain-dependent objects related to the new application.

    摘要翻译: 公开了一种用于设计标签指南的方法,用于标签机用于标记用于训练用于应用的口语理解(SLU)模块的数据。 该方法包括标签指导者设计者,其选择适用于应用的独立于领域的动作,根据应用的特征来选择依赖于域的对象,以及使用所选择的与域无关的动作和选择的域相关对象来生成标签指南。 以这种方式生成的标签指南的优点是,标签指南设计者可以通过选择一组独立于领域的动作,然后选择与新应用相关的域相关对象,轻松地将标签指南移植到新应用。

    SYSTEM FOR HANDLING FREQUENTLY ASKED QUESTIONS IN A NATURAL LANGUAGE DIALOG SERVICE
    5.
    发明申请
    SYSTEM FOR HANDLING FREQUENTLY ASKED QUESTIONS IN A NATURAL LANGUAGE DIALOG SERVICE 审中-公开
    在自然语言对话服务中处理常见问题的系统

    公开(公告)号:US20090070113A1

    公开(公告)日:2009-03-12

    申请号:US12266835

    申请日:2008-11-07

    IPC分类号: G10L15/18

    CPC分类号: G10L15/22 G06F3/167

    摘要: A voice-enabled help desk service is disclosed. The service comprises an automatic speech recognition module for recognizing speech from a user, a spoken language understanding module for understanding the output from the automatic speech recognition module, a dialog management module for generating a response to speech from the user, a natural voices text-to-speech synthesis module for synthesizing speech to generate the response to the user, and a frequently asked questions module. The frequently asked questions module handles frequently asked questions from the user by changing voices and providing predetermined prompts to answer the frequently asked question.

    摘要翻译: 公开了支持语音的帮助台服务。 该服务包括用于识别来自用户的语音的自动语音识别模块,用于理解来自自动语音识别模块的输出的口语语言理解模块,用于生成来自用户对语音的响应的对话管理模块,自然语音文本 - 语音合成模块,用于合成语音以产生对用户的响应,以及常见问题模块。 常见问题模块通过改变语音来处理用户的常见问题,并提供预定的提示来回答常见问题。

    METHOD FOR BUILDING A NATURAL LANGUAGE UNDERSTANDING MODEL FOR A SPOKEN DIALOG SYSTEM
    6.
    发明申请
    METHOD FOR BUILDING A NATURAL LANGUAGE UNDERSTANDING MODEL FOR A SPOKEN DIALOG SYSTEM 有权
    用于建立自然语言的方法来理解对讲机系统的模型

    公开(公告)号:US20100042404A1

    公开(公告)日:2010-02-18

    申请号:US12582062

    申请日:2009-10-20

    IPC分类号: G10L15/18 G06F17/27

    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。

    Method for building a natural language understanding model for a spoken dialog system
    8.
    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:US07620550B1

    公开(公告)日:2009-11-17

    申请号:US11866685

    申请日:2007-10-03

    IPC分类号: G10L15/18

    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。

    System and method of spoken language understanding in a spoken dialog service
    9.
    发明授权
    System and method of spoken language understanding in a spoken dialog service 有权
    口语对话服务中口语理解的系统和方法

    公开(公告)号:US07451089B1

    公开(公告)日:2008-11-11

    申请号:US11675166

    申请日:2007-02-15

    IPC分类号: G10L11/00 G10L21/00

    CPC分类号: G10L15/22 G06F3/167

    摘要: A voice-enabled help desk service is disclosed. The service comprises an automatic speech recognition module for recognizing speech from a user, a spoken language understanding module for understanding the output from the automatic speech recognition module, a dialog management module for generating a response to speech from the user, a natural voices text-to-speech synthesis module for synthesizing speech to generate the response to the user, and a frequently asked questions module. The frequently asked questions module handles frequently asked questions from the user by changing voices and providing predetermined prompts to answer the frequently asked question.

    摘要翻译: 公开了支持语音的帮助台服务。 该服务包括用于识别来自用户的语音的自动语音识别模块,用于理解来自自动语音识别模块的输出的口语语言理解模块,用于生成来自用户对语音的响应的对话管理模块,自然语音文本 - 语音合成模块,用于合成语音以产生对用户的响应,以及常见问题模块。 常见问题模块通过改变语音来处理用户的常见问题,并提供预定的提示来回答常见问题。

    SYSTEM AND METHOD OF SPOKEN LANGUAGE UNDERSTANDING IN HUMAN COMPUTER DIALOGS
    10.
    发明申请
    SYSTEM AND METHOD OF SPOKEN LANGUAGE UNDERSTANDING IN HUMAN COMPUTER DIALOGS 有权
    人类语言对话中语言语言理解的系统与方法

    公开(公告)号:US20120239383A1

    公开(公告)日:2012-09-20

    申请号:US13481031

    申请日:2012-05-25

    IPC分类号: G06F17/27 G10L15/00

    摘要: A system and method are disclosed that improve automatic speech recognition in a spoken dialog system. The method comprises partitioning speech recognizer output into self-contained clauses, identifying a dialog act in each of the self-contained clauses, qualifying dialog acts by identifying a current domain object and/or a current domain action, and determining whether further qualification is possible for the current domain object and/or current domain action. If further qualification is possible, then the method comprises identifying another domain action and/or another domain object associated with the current domain object and/or current domain action, reassigning the another domain action and/or another domain object as the current domain action and/or current domain object and then recursively qualifying the new current domain action and/or current object. This process continues until nothing is left to qualify.

    摘要翻译: 公开了一种提高口语对话系统中的自动语音识别的系统和方法。 该方法包括将语音识别器输出划分为独立子句,识别每个自包含子句中的对话行为,通过识别当前域对象和/或当前域动作进行限定对话行为,以及确定是否可进行进一步的限定 对于当前域对象和/或当前域操作。 如果可以进一步鉴定,则该方法包括识别与当前域对象和/或当前域操作相关联的另一域操作和/或另一域对象,将另一域操作和/或另一域对象重新分配为当前域操作,以及 /或当前域对象,然后递归地限定新的当前域操作和/或当前对象。 这个过程一直持续到没有什么是剩下的资格。