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公开(公告)号：US20110282648A1
公开(公告)日：2011-11-17
申请号：US12779751
申请日：2010-05-13
CPC分类号： G06F17/2818
摘要： A method of identifying and using side information available to statistical machine translation systems within an enterprise setting, the method including extracting user-specific interaction and non-interaction-based information from at least one corresponding database within the enterprise for each of a plurality of users, aggregating the user-specific interaction and non-interaction based information from a plurality of users, by using a processor on a computer, to tune and adapt background translation and language models, and updating all relevant models within the enterprise after user activity based on the tuned and adapted translation and language models.
摘要翻译： 一种识别和使用可用于企业设置内的统计机器翻译系统的侧面信息的方法，所述方法包括从多个用户中的每一个的企业内的至少一个对应的数据库中提取用户特定交互和非基于交互的信息 ，通过使用计算机上的处理器来聚合来自多个用户的用户特定交互和非基于交互的信息，以调整和适应背景翻译和语言模型，以及在基于用户活动的用户活动之后更新企业内的所有相关模型 调整和适应的翻译和语言模型。
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公开(公告)号：US08768686B2
公开(公告)日：2014-07-01
申请号：US12779751
申请日：2010-05-13
IPC分类号： G06F17/28
CPC分类号： G06F17/2818
摘要： A method of identifying and using side information available to statistical machine translation systems within an enterprise setting, the method including extracting user-specific interaction and non-interaction-based information from at least one corresponding database within the enterprise for each of a plurality of users, aggregating the user-specific interaction and non-interaction based information from a plurality of users, by using a processor on a computer, to tune and adapt background translation and language models, and updating all relevant models within the enterprise after user activity based on the tuned and adapted translation and language models.
摘要翻译： 一种识别和使用可用于企业设置内的统计机器翻译系统的侧面信息的方法，所述方法包括从多个用户中的每一个的企业内的至少一个对应的数据库中提取用户特定交互和非基于交互的信息 ，通过使用计算机上的处理器来聚合来自多个用户的用户特定交互和非基于交互的信息，以调整和适应背景翻译和语言模型，以及在基于用户活动的用户活动之后更新企业内的所有相关模型 调整和适应的翻译和语言模型。
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公开(公告)号：US20130073276A1
公开(公告)日：2013-03-21
申请号：US13236016
申请日：2011-09-19
申请人： Ruhi Sarikaya , Vaibhava Goel , David Nahamoo , Real Tremblay , Bhuvana Ramabhadran , Osamuyimen Stewart
发明人： Ruhi Sarikaya , Vaibhava Goel , David Nahamoo , Real Tremblay , Bhuvana Ramabhadran , Osamuyimen Stewart
IPC分类号： G06F17/28
CPC分类号： G06F17/289 , G10L15/22 , G10L15/26 , H04M3/42 , H04M3/42391 , H04M2242/12
摘要： Operation of an automated dialog system is described using a source language to conduct a real time human machine dialog process with a human user using a target language. A user query in the target language is received and automatically machine translated into the source language. An automated reply of the dialog process is then delivered to the user in the target language. If the dialog process reaches an initial assistance state, a first human agent using the source language is provided to interact in real time with the user in the target language by machine translation to continue the dialog process. Then if the dialog process reaches a further assistance state, a second human agent using the target language is provided to interact in real time with the user in the target language to continue the dialog process.
摘要翻译： 使用源语言来描述自动对话系统的操作，以使用目标语言与人类用户进行实时的人机对话过程。 接收目标语言的用户查询并自动机器翻译成源语言。 然后将对话过程的自动回复以目标语言传递给用户。 如果对话过程达到初始辅助状态，则使用源语言的第一人机代理被提供以通过机器翻译以目标语言与用户实时交互以继续对话过程。 然后，如果对话过程达到进一步的辅助状态，则使用目标语言的第二人机代理被提供以与目标语言的用户实时交互以继续对话过程。
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公开(公告)号：US09367526B1
公开(公告)日：2016-06-14
申请号：US13190891
申请日：2011-07-26
申请人： Paul Vozila , Maximilian Bisani , Yi Su , Stephen M. Chu , Stanley F. Chen , Ruhi Sarikaya , Bhuvana Ramabhadran
发明人： Paul Vozila , Maximilian Bisani , Yi Su , Stephen M. Chu , Stanley F. Chen , Ruhi Sarikaya , Bhuvana Ramabhadran
CPC分类号： G06F17/218 , G06F17/2775 , G06F17/2785 , G06F17/30663 , G06F17/30684 , G06F17/30687 , G06F17/30705 , G06F17/30707 , G06Q10/107
摘要： A language processing application employs a classing function optimized for the underlying production application context for which it is expected to process speech. A combination of class based and word based features generates a classing function optimized for a particular production application, meaning that a language model employing the classing function uses word classes having a high likelihood of accurately predicting word sequences encountered by a language model invoked by the production application. The classing function optimizes word classes by aligning the objective of word classing with the underlying language processing task to be performed by the production application. The classing function is optimized to correspond to usage in the production application context using class-based and word-based features by computing a likelihood of a word in an n-gram and a frequency of a word within a class of the n-gram.
摘要翻译： 语言处理应用程序使用针对其预期处理语音的底层生产应用程序环境进行优化的分类功能。 基于类和基于字的特征的组合产生针对特定生产应用优化的分类功能，这意味着采用分类函数的语言模型使用具有准确预测由生产调用的语言模型遇到的单词序列的高似然性的单词类 应用。 分类函数通过将单词分类的目标与生产应用程序执行的底层语言处理任务进行对齐来优化单词类。 通过计算n-gram中的单词和n-gram类中的单词的可能性，使用基于类和基于单词的特征来优化分类功能以对应于生产应用上下文中的使用。
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公开(公告)号：US09646001B2
公开(公告)日：2017-05-09
申请号：US13236016
申请日：2011-09-19
申请人： Ruhi Sarikaya , Vaibhava Goel , David Nahamoo , Rèal Tremblay , Bhuvana Ramabhadran , Osamuyimen Stewart
发明人： Ruhi Sarikaya , Vaibhava Goel , David Nahamoo , Rèal Tremblay , Bhuvana Ramabhadran , Osamuyimen Stewart
CPC分类号： G06F17/289 , G10L15/22 , G10L15/26 , H04M3/42 , H04M3/42391 , H04M2242/12
摘要： Operation of an automated dialog system is described using a source language to conduct a real time human machine dialog process with a human user using a target language. A user query in the target language is received and automatically machine translated into the source language. An automated reply of the dialog process is then delivered to the user in the target language. If the dialog process reaches an initial assistance state, a first human agent using the source language is provided to interact in real time with the user in the target language by machine translation to continue the dialog process. Then if the dialog process reaches a further assistance state, a second human agent using the target language is provided to interact in real time with the user in the target language to continue the dialog process.
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6.发明申请公开(公告)号：US20090063866A1
公开(公告)日：2009-03-05
申请号：US11846893
申请日：2007-08-29
申请人： Jiri Navratil , Bhuvana Ramabhadran
发明人： Jiri Navratil , Bhuvana Ramabhadran
CPC分类号： H04L63/0861 , A61B5/0484 , A61B5/04842 , A61B5/117 , G06F21/32 , G06F21/44 , G06F21/445 , H04L67/306
摘要： Techniques are disclosed for authentication and identification of a user by use of an electroencephalographic (EEG) signal. For example, a method for authenticating a user includes the following steps. At least one electroencephalographic response is obtained from a user in accordance with perceptory stimuli presented to the user. The user is authenticated based on the obtained electroencephalographic response. The authenticating step may be based on detection of an event-related potential in the obtained electroencephalographic response. The event-related potential may be a P300 event-related potential. The method may also include the step of enrolling the user prior to authenticating the user. The enrolling step may include a supervised enrollment procedure or an unsupervised enrollment procedure.
摘要翻译： 公开了通过使用脑电图（EEG）信号来认证和识别用户的技术。 例如，用于验证用户的方法包括以下步骤。 根据呈现给用户的感知刺激，从用户获得至少一个脑电图响应。 基于获得的脑电图响应来认证用户。 认证步骤可以基于所获得的脑电图响应中事件相关电位的检测。 事件相关的潜力可能是P300事件相关的潜力。 该方法还可以包括在认证用户之前注册用户的步骤。 注册步骤可以包括监督注册过程或无监督注册过程。
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7.发明授权公开(公告)号：US09058473B2
公开(公告)日：2015-06-16
申请号：US11846893
申请日：2007-08-29
申请人： Jiri Navratil , Bhuvana Ramabhadran
发明人： Jiri Navratil , Bhuvana Ramabhadran
CPC分类号： H04L63/0861 , A61B5/0484 , A61B5/04842 , A61B5/117 , G06F21/32 , G06F21/44 , G06F21/445 , H04L67/306
摘要： Techniques are disclosed for authentication and identification of a user by use of an electroencephalographic (EEG) signal. For example, a method for authenticating a user includes the following steps. At least one electroencephalographic response is obtained from a user in accordance with perceptory stimuli presented to the user. The user is authenticated based on the obtained electroencephalographic response. The authenticating step may be based on detection of an event-related potential in the obtained electroencephalographic response. The event-related potential may be a P300 event-related potential. The method may also include the step of enrolling the user prior to authenticating the user. The enrolling step may include a supervised enrollment procedure or an unsupervised enrollment procedure.
摘要翻译： 公开了通过使用脑电图（EEG）信号来认证和识别用户的技术。 例如，用于验证用户的方法包括以下步骤。 根据呈现给用户的感知刺激，从用户获得至少一个脑电图响应。 基于获得的脑电图响应来认证用户。 认证步骤可以基于所获得的脑电图响应中事件相关电位的检测。 事件相关的潜力可能是P300事件相关的潜力。 该方法还可以包括在认证用户之前注册用户的步骤。 注册步骤可以包括监督注册过程或无监督注册过程。
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公开(公告)号：US09054666B2
公开(公告)日：2015-06-09
申请号：US13448428
申请日：2012-04-17
CPC分类号： H03G3/32
摘要： A method for improving the performance of a noise cancellation device, the method includes determining whether one or more noise making objects (NMO) are near an audible range of the noise cancellation device and receiving a signal from the one or more NMOs indicative of a kind of noise the one or more NMOs is generating. The method also includes selecting a specific noise cancellation model to reduce an expected noise in response to the received kind of noise the one or more NMOs is generating.
摘要翻译： 一种用于改善噪声消除装置的性能的方法，所述方法包括确定一个或多个噪声产生对象（NMO）是否在噪声消除装置的可听范围附近并且接收来自指示某种类型的一个或多个NMO的信号 一个或多个NMO正在产生噪音。 该方法还包括选择特定的噪声消除模型以响应于所接收的一个或多个NMO产生的噪声种类来减少期望的噪声。
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公开(公告)号：US20140164299A1
公开(公告)日：2014-06-12
申请号：US13707088
申请日：2012-12-06
IPC分类号： G06N3/08
CPC分类号： G06N3/08
摘要： Pretraining for a DBN initializes weights of the DBN (Deep Belief Network) using a hybrid pre-training methodology. Hybrid pre-training employs generative component that allows the hybrid PT method to have better performance in WER (Word Error Rate) compared to the discriminative PT method. Hybrid pre-training learns weights which are more closely linked to the final objective function, allowing for a much larger batch size compared to generative PT, which allows for improvements in speed; and a larger batch size allows for parallelization of the gradient computation, speeding up training further.
摘要翻译： 预先训练DBN使用混合预训练方法初始化DBN（深信仰网络）的权重。 混合预训练采用生成部件，与辨别性PT方法相比，允许混合PT方法在WER（字错误率）方面具有更好的性能。 混合预训练学习与最终目标函数更紧密相关的权重，允许与生成PT相比更大的批量大小，这允许提高速度; 并且较大的批量允许梯度计算的并行化，进一步加速训练。
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10.发明授权公开(公告)号：US08655644B2
公开(公告)日：2014-02-18
申请号：US12570665
申请日：2009-09-30
IPC分类号： G06F17/28
CPC分类号： G06F17/289 , G06Q20/102
摘要： Methods and apparatus for language translation in a computing environment associated with a virtual application are presented. For example, a method for providing language translation includes determining languages of a user and a correspondent; determining one or more sequences of translators; determining a selected sequence of selected translators from the one or more sequences of the translators; requesting a change in virtual locations, within the computing environment associated with the virtual application, of one or more selected translator virtual representations of the selected translators to a virtual meeting location within the computing environment associated with the virtual application; and changing virtual locations of the one or more selected translator virtual representations to the virtual meeting location. One or more of determining languages, determining one or more sequences, determining a selected sequence, requesting a change in virtual locations, and changing virtual locations occur on a processor device.
摘要翻译： 提出了与虚拟应用程序相关联的计算环境中的语言翻译的方法和装置。 例如，提供语言翻译的方法包括确定用户和记者的语言; 确定翻译器的一个或多个序列; 从所述翻译器的所述一个或多个序列确定所选择的翻译器的选定序列; 在与所述虚拟应用相关联的所述计算环境内，将所选择的转换器的一个或多个所选择的转换器虚拟表示的虚拟位置改变为与所述虚拟应用相关联的所述计算环境内的虚拟会议位置; 以及将所述一个或多个所选择的翻译器虚拟表示的虚拟位置改变到所述虚拟会议位置。 确定一个或多个序列，确定所选择的序列，请求虚拟位置的改变以及改变虚拟位置中的一个或多个发生在处理器设备上。
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