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11. 发明申请

US20100124325A1 System and Method for Interacting with Live Agents in an Automated Call Center 有权
标题翻译：在自动呼叫中心与实时代理交互的系统和方法
公开(公告)号：US20100124325A1
公开(公告)日：2010-05-20
申请号：US12274258
申请日：2008-11-19
申请人： Fuliang Weng , Baoshi Yan , Zhongnan Shen , Zhe Feng , Kui Xu , Katrina Li
发明人： Fuliang Weng , Baoshi Yan , Zhongnan Shen , Zhe Feng , Kui Xu , Katrina Li
IPC分类号： H04M3/00 , G10L15/04
CPC分类号： H04M3/5166 , G10L15/22 , H04M2201/40
摘要： Embodiments of an interface system that enables a call center agent to access and intervene in an interaction between an automated call center system and a caller whenever necessary for complex application tasks is described. The system includes a user interface that presents the agent with one or more categories of information, including the conversation flow, obtained semantic information, the recognized utterances, and access to the utterance waveforms. This information is cross-linked and attached with a confidence level for better access and navigation within the dialog system for the generation of appropriate responses to the caller.
摘要翻译：描述了使得呼叫中心代理能够访问并介入自动呼叫中心系统和呼叫者之间的交互的接口系统的实施例，以便在需要复杂的应用任务时。该系统包括用户界面，其向代理呈现一个或多个类别的信息，包括会话流，获得的语义信息，识别的话语和对话音波形的访问。该信息是交叉链接的，并附有置信水平，以便在对话系统内更好地访问和导航以产生对呼叫者的适当响应。

12. 发明授权

US10209853B2 System and method for dialog-enabled context-dependent and user-centric content presentation 有权
公开(公告)号：US10209853B2
公开(公告)日：2019-02-19
申请号：US15104695
申请日：2014-12-11
申请人： Robert Bosch GmbH , Fuliang Weng , Kui Xu , Fei Liu , Lin Zhao , Zhe Feng , Zhongnan Shen
发明人： Fuliang Weng , Kui Xu , Fei Liu , Lin Zhao , Zhe Feng , Zhongnan Shen
IPC分类号： G06F3/0481 , G06F9/451 , G06F3/01 , G06Q30/02 , G10L15/22 , G06F3/0488 , B60K35/00 , H04L29/06 , H04L29/08
摘要： An in-vehicle infotainment system, smart home information access and device control unit, or mobile system presents summarized information to a user based on a user preference model that is associated with the user. The system modifies the presentation of information to the user based on environmental context data about the vehicle and user context data about the activity of the user. During presentation of the information, the system modifies the content and presentation of the summarized information in response to multi-modal input requests from the user.

13. 发明授权

US08943394B2 System and method for interacting with live agents in an automated call center 有权
标题翻译：在自动呼叫中心与实时代理交互的系统和方法
公开(公告)号：US08943394B2
公开(公告)日：2015-01-27
申请号：US12274258
申请日：2008-11-19
申请人： Fuliang Weng , Baoshi Yan , Zhongnan Shen , Zhe Feng , Kui Xu , Katrina Li
发明人： Fuliang Weng , Baoshi Yan , Zhongnan Shen , Zhe Feng , Kui Xu , Katrina Li
IPC分类号： G06F17/00 , G06F17/20 , G06F17/21 , G06F17/22 , G06F17/24 , G06F17/25 , G06F17/26 , G06F17/27 , G06F17/28 , G10L15/00 , G10L15/04 , G10L21/00 , H04M3/51 , G10L15/22
CPC分类号： H04M3/5166 , G10L15/22 , H04M2201/40
摘要： Embodiments of an interface system that enables a call center agent to access and intervene in an interaction between an automated call center system and a caller whenever necessary for complex application tasks is described. The system includes a user interface that presents the agent with one or more categories of information, including the conversation flow, obtained semantic information, the recognized utterances, and access to the utterance waveforms. This information is cross-linked and attached with a confidence level for better access and navigation within the dialog system for the generation of appropriate responses to the caller.
摘要翻译：描述了使得呼叫中心代理能够访问并介入自动呼叫中心系统和呼叫者之间的交互的接口系统的实施例，以便在需要复杂的应用任务时。该系统包括用户界面，其向代理呈现一个或多个类别的信息，包括会话流，获得的语义信息，识别的话语和对话音波形的访问。该信息是交叉链接的，并附有置信水平，以便在对话系统内更好地访问和导航以产生对呼叫者的适当响应。

14. 发明申请

US20080154578A1 Method and system for learning ontological relations from documents 有权
标题翻译：从文件学习本体论关系的方法和系统
公开(公告)号：US20080154578A1
公开(公告)日：2008-06-26
申请号：US11645386
申请日：2006-12-26
申请人： Kui Xu , Fuliang Weng
发明人： Kui Xu , Fuliang Weng
IPC分类号： G10L13/08
CPC分类号： G10L15/1815 , G10L15/183 , Y10S707/99933 , Y10S707/99936 , Y10S707/99942
摘要： Embodiments of an ontological determination method for use in natural language processing applications are described. In one embodiment, shallow lexico-syntactic patterns are applied to identify relations by extracting term features to distinguish relation terms from non-relation terms, identifying coordinate relations for every adjacent terms; identifying short-distance ontological (e.g., hypernym or part-whole relations) for other adjacent terms based on term features and lexico-syntactic patterns; and then inferring long-distance hypernym and part-whole relations based on the identified coordinate relations and the short-distance relations.
摘要翻译：描述了在自然语言处理应用中使用的本体确定方法的实施例。在一个实施例中，应用浅层词典模式以通过提取术语特征来识别关系，以将关系项与非关系术语区分开来，识别每个相邻术语的坐标关系; 基于术语特征和词典语法模式识别其他相邻术语的短距离本体论（例如，超音阶或部分整体关系）; 然后根据确定的协调关系和短距离关系推断出长距离超高和部分整体关系。

15. 发明授权

US08972260B2 Speech recognition using multiple language models 有权
标题翻译：多语言模型的语音识别
公开(公告)号：US08972260B2
公开(公告)日：2015-03-03
申请号：US13450861
申请日：2012-04-19
申请人： Fuliang Weng , Zhe Feng , Kui Xu , Lin Zhao
发明人： Fuliang Weng , Zhe Feng , Kui Xu , Lin Zhao
IPC分类号： G10L15/00 , G10L15/32 , G10L15/06 , G10L15/18 , G10L15/193 , G10L15/197 , G10L15/30
CPC分类号： G10L15/32 , G10L15/063 , G10L15/18 , G10L15/193 , G10L15/197 , G10L15/30
摘要： In accordance with one embodiment, a method of generating language models for speech recognition includes identifying a plurality of utterances in training data corresponding to speech, generating a frequency count of each utterance in the plurality of utterances, generating a high-frequency plurality of utterances from the plurality of utterances having a frequency that exceeds a predetermined frequency threshold, generating a low-frequency plurality of utterances from the plurality of utterances having a frequency that is below the predetermined frequency threshold, generating a grammar-based language model using the high-frequency plurality of utterances as training data, and generating a statistical language model using the low-frequency plurality of utterances as training data.
摘要翻译：根据一个实施例，一种生成用于语音识别的语言模型的方法包括：识别与语音相对应的训练数据中的多个话语，产生多个话语中的每个发声的频率计数，从多个话语中产生高频多个话语所述多个话音具有超过预定频率阈值的频率，从具有低于所述预定频率阈值的频率的所述多个话语中产生低频多个话语，使用所述高频率生成基于语法的语言模型多个话语作为训练数据，并且使用低频多个话语生成统计语言模型作为训练数据。

16. 发明申请

US20120271631A1 SPEECH RECOGNITION USING MULTIPLE LANGUAGE MODELS 有权
标题翻译：使用多种语言模型进行语音识别
公开(公告)号：US20120271631A1
公开(公告)日：2012-10-25
申请号：US13450861
申请日：2012-04-19
申请人： Fuliang Weng , Zhe Feng , Kui Xu , Lin Zhao
发明人： Fuliang Weng , Zhe Feng , Kui Xu , Lin Zhao
IPC分类号： G10L15/06
CPC分类号： G10L15/32 , G10L15/063 , G10L15/18 , G10L15/193 , G10L15/197 , G10L15/30
摘要： In accordance with one embodiment, a method of generating language models for speech recognition includes identifying a plurality of utterances in training data corresponding to speech, generating a frequency count of each utterance in the plurality of utterances, generating a high-frequency plurality of utterances from the plurality of utterances having a frequency that exceeds a predetermined frequency threshold, generating a low-frequency plurality of utterances from the plurality of utterances having a frequency that is below the predetermined frequency threshold, generating a grammar-based language model using the high-frequency plurality of utterances as training data, and generating a statistical language model using the low-frequency plurality of utterances as training data.
摘要翻译：根据一个实施例，一种生成用于语音识别的语言模型的方法包括：识别与语音相对应的训练数据中的多个话语，产生多个话语中的每个发声的频率计数，从多个话语中产生高频多个话语所述多个话音具有超过预定频率阈值的频率，从具有低于所述预定频率阈值的频率的所述多个话语中产生低频多个话语，使用所述高频率生成基于语法的语言模型多个话语作为训练数据，并且使用低频多个话语生成统计语言模型作为训练数据。

17. 发明授权

US08019594B2 Method and apparatus for progressively selecting features from a large feature space in statistical modeling 有权
标题翻译：在统计建模中从大特征空间逐步选择特征的方法和装置
公开(公告)号：US08019594B2
公开(公告)日：2011-09-13
申请号：US11478990
申请日：2006-06-30
申请人： Fuliang Weng , Zhe Feng , Qi Zhang
发明人： Fuliang Weng , Zhe Feng , Qi Zhang
IPC分类号： G06F17/27
CPC分类号： G06F17/277 , G06K9/6228 , G10L15/02 , G10L15/063
摘要： Embodiments of a progressive feature selection method that selects features in multiple rounds are described. In one embodiment, the progressive feature selection method splits the feature space into tractable sub-spaces such that a feature selection algorithm can be performed on each sub-space. In a merge-split operation, the subset of features that the feature selection algorithm selects from the different sub-spaces are merged into subsequent sets of features. Instead of re-generating the mapping table for each subsequent set from scratch, a new mapping table from the previous round's tables is created by collecting those entries that correspond to the selected features. The feature selection method is then performed again on each of the subsequent feature sets and new features are selected from each of these feature sets. This feature selection-merge-split process is repeated on successively smaller numbers of feature sets until a single final set of features is selected.
摘要翻译：描述了选择多个轮中的特征的渐进特征选择方法的实施例。在一个实施例中，逐行特征选择方法将特征空间分解成易处理的子空间，使得可以对每个子空间执行特征选择算法。在合并分割操作中，特征选择算法从不同子空间中选择的特征子集被合并到随后的特征集中。不是从头重新生成每个后续集合的映射表，而是通过收集与所选特征相对应的条目来创建来自前一轮的表的新映射表。然后在每个后续特征集上再次执行特征选择方法，并且从这些特征集中的每一个中选择新特征。在连续较小数量的特征集上重复该特征选择合并分割处理，直到选择单个最终特征集。

18. 发明授权

US08019593B2 Method and apparatus for generating features through logical and functional operations 有权
标题翻译：用于通过逻辑和功能操作产生特征的方法和装置
公开(公告)号：US08019593B2
公开(公告)日：2011-09-13
申请号：US11478989
申请日：2006-06-30
申请人： Fuliang Weng , Zhe Feng , Qi Zhang
发明人： Fuliang Weng , Zhe Feng , Qi Zhang
IPC分类号： G06F17/27
CPC分类号： G10L15/18 , G06K9/6228 , G06K9/6232 , G10L15/02
摘要： Embodiments of a feature generation system and process for use in machine learning applications utilizing statistical modeling systems are described. In one embodiment, the feature generation process generates large feature spaces by combining features using logical, arithmetic and/or functional operations. A first set of features in an initial feature space are defined. Some or all of the first set of features are processed using one or more arithmetic, logic, user-defined combinatorial processes, or combinations thereof, to produce additional features. The additional features and at least some of the first set of features are combined to produce an expanded feature space. The expanded feature space is processed through a feature selection and optimization process to produce a model in a statistical modeling system.
摘要翻译：描述了使用统计建模系统的特征生成系统和用于机器学习应用的过程的实施例。在一个实施例中，特征生成过程通过使用逻辑，算术和/或功能操作组合特征来生成大的特征空间。定义初始特征空间中的第一组特征。使用一个或多个算术，逻辑，用户定义的组合过程或其组合来处理第一组特征中的一些或全部，以产生附加特征。附加特征和第一组特征中的至少一些被组合以产生扩展的特征空间。扩展的特征空间通过特征选择和优化过程进行处理，以在统计建模系统中产生模型。

19. 发明授权

US07788094B2 Apparatus, method and system for maximum entropy modeling for uncertain observations 有权
标题翻译：用于不确定性观测的最大熵建模的装置，方法和系统
公开(公告)号：US07788094B2
公开(公告)日：2010-08-31
申请号：US11699891
申请日：2007-01-29
申请人： Farhad Farahani , Fuliang Weng , Qi Zhang
发明人： Farhad Farahani , Fuliang Weng , Qi Zhang
IPC分类号： G10L15/00 , G10L15/18 , G06F17/27 , G06F7/60 , G06F17/18 , G06F17/00 , G06F5/00
CPC分类号： G06F17/2715 , G10L2015/0635
摘要： A method for performing conditional maximum entropy modeling includes constructing a conditional maximum entropy model, and incorporating an observation confidence score into the model to reduce an effect due to an uncertain observation.
摘要翻译：用于执行条件最大熵建模的方法包括构建条件最大熵模型，并将观察置信度分数并入模型中以减少由于不确定观察而产生的影响。

20. 发明申请

US20080004865A1 Method and apparatus for progressively selecting features from a large feature space in statistical modeling 有权
标题翻译：在统计建模中从大特征空间逐步选择特征的方法和装置
公开(公告)号：US20080004865A1
公开(公告)日：2008-01-03
申请号：US11478990
申请日：2006-06-30
申请人： Fuliang Weng , Zhe Feng , Qi Zhang
发明人： Fuliang Weng , Zhe Feng , Qi Zhang
IPC分类号： G06F17/27
CPC分类号： G06F17/277 , G06K9/6228 , G10L15/02 , G10L15/063
摘要： Embodiments of a progressive feature selection method that selects features in multiple rounds are described. In one embodiment, the progressive feature selection method splits the feature space into tractable sub-spaces such that a feature selection algorithm can be performed on each sub-space. In a merge-split operation, the subset of features that the feature selection algorithm selects from the different sub-spaces are merged into subsequent sets of features. Instead of re-generating the mapping table for each subsequent set from scratch, a new mapping table from the previous round's tables is created by collecting those entries that correspond to the selected features. The feature selection method is then performed again on each of the subsequent feature sets and new features are selected from each of these feature sets. This feature selection-merge-split process is repeated on successively smaller numbers of feature sets until a single final set of features is selected.
摘要翻译：描述了选择多个轮中的特征的渐进特征选择方法的实施例。在一个实施例中，逐行特征选择方法将特征空间分解成易处理的子空间，使得可以对每个子空间执行特征选择算法。在合并分割操作中，特征选择算法从不同子空间中选择的特征子集被合并到随后的特征集中。不是从头重新生成每个后续集合的映射表，而是通过收集与所选特征相对应的条目来创建来自前一轮的表的新映射表。然后在每个后续特征集上再次执行特征选择方法，并且从这些特征集中的每一个中选择新特征。在连续较小数量的特征集上重复该特征选择合并分割处理，直到选择单个最终特征集。

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