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1.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
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。
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2.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
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。
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3.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
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。
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4.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：US07295981B1
公开(公告)日：2007-11-13
申请号：US10755014
申请日：2004-01-09
IPC分类号： G10L15/18
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。
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5.发明授权公开(公告)号：US08190436B2
公开(公告)日：2012-05-29
申请号：US10310596
申请日：2002-12-05
CPC分类号： G10L15/1815 , G06F17/2785 , G10L13/043 , G10L15/02 , G10L15/1822 , G10L15/265
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，以及确定是否可进一步限定 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。
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公开(公告)号：US08849648B1
公开(公告)日：2014-09-30
申请号：US10329138
申请日：2002-12-24
IPC分类号： G06F17/27
CPC分类号： G06F17/2705 , G06F17/218 , G06F17/27 , G06F17/2775 , G10L15/05 , G10L15/26 , G10L2015/025 , G10L2015/081 , G10L2015/088
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.
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公开(公告)号：US08818793B1
公开(公告)日：2014-08-26
申请号：US10446489
申请日：2003-05-28
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。
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公开(公告)号：US07729902B1
公开(公告)日：2010-06-01
申请号：US11927738
申请日：2007-10-30
CPC分类号： G06F17/279 , G10L15/18 , G10L15/183
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。
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9.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
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。
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公开(公告)号：US08386262B2
公开(公告)日：2013-02-26
申请号：US13481031
申请日：2012-05-25
CPC分类号： G10L15/1815 , G06F17/2785 , G10L13/043 , G10L15/02 , G10L15/1822 , G10L15/265
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.
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