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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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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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3.发明授权System and method for optimizing pattern recognition of non-gaussian parameters 有权用于优化非高斯参数的模式识别的系统和方法公开(公告)号：US08185480B2
公开(公告)日：2012-05-22
申请号：US12061023
申请日：2008-04-02
IPC分类号： G06F15/18
CPC分类号： G06K9/6226
摘要： A method of optimizing a function of a parameter includes associating, with an objective function for initial value of parameters, an auxiliary function of parameters that could be optimized computationally more efficiently than an original objective function, obtaining parameters that are optimum for the auxiliary function, obtaining updated parameters by taking a weighted sum of the optimum of the auxiliary function and initial model parameters.
摘要翻译： 一种优化参数函数的方法包括将参数初始值的目标函数与原始目标函数的计算效率进行优化的参数辅助函数相关联，获得对辅助函数最佳的参数， 通过获取辅助功能和初始模型参数的最优值的加权和获得更新的参数。
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公开(公告)号：US08484024B2
公开(公告)日：2013-07-09
申请号：US13034293
申请日：2011-02-24
IPC分类号： G10L15/06
CPC分类号： G10L15/063 , G10L15/02 , G10L15/083 , G10L2015/025 , G10L2015/0631
摘要： Techniques are disclosed for using phonetic features for speech recognition. For example, a method comprises the steps of obtaining a first dictionary and a training data set associated with a speech recognition system, computing one or more support parameters from the training data set, transforming the first dictionary into a second dictionary, wherein the second dictionary is a function of one or more phonetic labels of the first dictionary, and using the one or more support parameters to select one or more samples from the second dictionary to create a set of one or more exemplar-based class identification features for a pattern recognition task.
摘要翻译： 公开了使用语音特征进行语音识别的技术。 例如，一种方法包括以下步骤：获得与语音识别系统相关联的第一字典和训练数据集，从训练数据集计算一个或多个支持参数，将第一字典变换为第二字典，其中第二字典 是第一字典的一个或多个语音标签的功能，并且使用一个或多个支持参数从第二字典中选择一个或多个样本，以创建用于模式识别的一个或多个基于样本的类识别特征的集合 任务。
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公开(公告)号：US20120221333A1
公开(公告)日：2012-08-30
申请号：US13034293
申请日：2011-02-24
IPC分类号： G10L15/06
CPC分类号： G10L15/063 , G10L15/02 , G10L15/083 , G10L2015/025 , G10L2015/0631
摘要： Techniques are disclosed for using phonetic features for speech recognition. For example, a method comprises the steps of obtaining a first dictionary and a training data set associated with a speech recognition system, computing one or more support parameters from the training data set, transforming the first dictionary into a second dictionary, wherein the second dictionary is a function of one or more phonetic labels of the first dictionary, and using the one or more support parameters to select one or more samples from the second dictionary to create a set of one or more exemplar-based class identification features for a pattern recognition task.
摘要翻译： 公开了使用语音特征进行语音识别的技术。 例如，一种方法包括以下步骤：获得与语音识别系统相关联的第一字典和训练数据集，从训练数据集计算一个或多个支持参数，将第一字典变换为第二字典，其中第二字典 是第一字典的一个或多个语音标签的功能，并且使用一个或多个支持参数从第二字典中选择一个或多个样本，以创建用于模式识别的一个或多个基于样本的类识别特征的集合 任务。
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公开(公告)号：US20110282925A1
公开(公告)日：2011-11-17
申请号：US12777768
申请日：2010-05-11
CPC分类号： G06F17/11
摘要： An optimization system and method includes determining a best gradient as a sparse direction in a function having a plurality of parameters. The sparse direction includes a direction that maximizes change of the function. This maximum change of the function is determined by performing an optimization process that gives maximum growth subject to a sparsity regularized constraint. An extended Baum Welch (EBW) method can be used to identify the sparse direction. A best step size is determined along the sparse direction by finding magnitudes of entries of direction that maximizes the function restricted to the sparse direction. A solution is recursively refined for the function optimization using a processor and storage media.
摘要翻译： 优化系统和方法包括在具有多个参数的函数中确定最佳梯度作为稀疏方向。 稀疏方向包括使功能变化最大化的方向。 通过执行优化处理来确定功能的最大变化，该优化过程允许受到稀疏正则化约束的最大增长。 扩展的Baum Welch（EBW）方法可用于识别稀疏方向。 通过找到使限于稀疏方向的功能最大化的方向条目的大小，沿着稀疏方向确定最佳步长。 使用处理器和存储介质递归地优化了功能优化的解决方案。
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公开(公告)号：US08527566B2
公开(公告)日：2013-09-03
申请号：US12777768
申请日：2010-05-11
IPC分类号： G06F7/00
CPC分类号： G06F17/11
摘要： An optimization system and method includes determining a best gradient as a sparse direction in a function having a plurality of parameters. The sparse direction includes a direction that maximizes change of the function. This maximum change of the function is determined by performing an optimization process that gives maximum growth subject to a sparsity regularized constraint. An extended Baum Welch (EBW) method can be used to identify the sparse direction. A best step size is determined along the sparse direction by finding magnitudes of entries of direction that maximizes the function restricted to the sparse direction. A solution is recursively refined for the function optimization using a processor and storage media.
摘要翻译： 优化系统和方法包括在具有多个参数的函数中确定最佳梯度作为稀疏方向。 稀疏方向包括使功能变化最大化的方向。 通过执行优化处理来确定功能的最大变化，该优化过程允许受到稀疏正则化约束的最大增长。 扩展的Baum Welch（EBW）方法可用于识别稀疏方向。 通过找到使限于稀疏方向的功能最大化的方向条目的大小，沿着稀疏方向确定最佳步长。 使用处理器和存储介质递归地优化了功能优化的解决方案。
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公开(公告)号：US20120078621A1
公开(公告)日：2012-03-29
申请号：US12889845
申请日：2010-09-24
IPC分类号： G10L15/00
CPC分类号： G10L15/02
摘要： Techniques are disclosed for generating and using sparse representation features to improve speech recognition performance. In particular, principles of the invention provide sparse representation exemplar-based recognition techniques. For example, a method comprises the following steps. A test vector and a training data set associated with a speech recognition system are obtained. A subset of the training data set is selected. The test vector is mapped with the selected subset of the training data set as a linear combination that is weighted by a sparseness constraint such that a new test feature set is formed wherein the training data set is moved more closely to the test vector subject to the sparseness constraint. An acoustic model is trained on the new test feature set.The acoustic model trained on the new test feature set may be used to decode user speech input to the speech recognition system.
摘要翻译： 公开了用于生成和使用稀疏表示特征以改善语音识别性能的技术。 特别地，本发明的原理提供了基于示例的稀疏表示识别技术。 例如，一种方法包括以下步骤。 获得与语音识别系统相关联的测试向量和训练数据集。 选择训练数据集的子集。 将测试向量与所选择的训练数据集的子集映射为由稀疏约束加权的线性组合，使得形成新的测试特征集合，其中训练数据集更接近地移动到受测对象的测试向量 稀疏约束 在新的测试功能集上训练声学模型。 在新测试特征集上训练的声学模型可以用于解码输入到语音识别系统的用户语音。
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公开(公告)号：US08484023B2
公开(公告)日：2013-07-09
申请号：US12889845
申请日：2010-09-24
IPC分类号： G10L15/06
CPC分类号： G10L15/02
摘要： Techniques are disclosed for generating and using sparse representation features to improve speech recognition performance. In particular, principles of the invention provide sparse representation exemplar-based recognition techniques. For example, a method comprises the following steps. A test vector and a training data set associated with a speech recognition system are obtained. A subset of the training data set is selected. The test vector is mapped with the selected subset of the training data set as a linear combination that is weighted by a sparseness constraint such that a new test feature set is formed wherein the training data set is moved more closely to the test vector subject to the sparseness constraint. An acoustic model is trained on the new test feature set. The acoustic model trained on the new test feature set may be used to decode user speech input to the speech recognition system.
摘要翻译： 公开了用于生成和使用稀疏表示特征以改善语音识别性能的技术。 特别地，本发明的原理提供了基于示例的稀疏表示识别技术。 例如，一种方法包括以下步骤。 获得与语音识别系统相关联的测试向量和训练数据集。 选择训练数据集的子集。 将测试向量与所选择的训练数据集的子集映射为由稀疏约束加权的线性组合，使得形成新的测试特征集合，其中训练数据集更接近地移动到受测对象的测试向量 稀疏约束 在新的测试功能集上训练声学模型。 在新测试特征集上训练的声学模型可以用于解码输入到语音识别系统的用户语音。
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公开(公告)号：US20120290299A1
公开(公告)日：2012-11-15
申请号：US13107001
申请日：2011-05-13
申请人： Sara H. Basson , Rick Hamilton , Dan Ning Jiang , Dimitri Kanevsky , David Nahamoo , Michael Picheny , Bhuvana Ramabhadran , Tara N. Sainath
发明人： Sara H. Basson , Rick Hamilton , Dan Ning Jiang , Dimitri Kanevsky , David Nahamoo , Michael Picheny , Bhuvana Ramabhadran , Tara N. Sainath
IPC分类号： G10L15/26
CPC分类号： G06F17/28 , G06F17/2785 , G06F17/289 , G10L15/063 , G10L15/26
摘要： Techniques for converting spoken speech into written speech are provided. The techniques include transcribing input speech via speech recognition, mapping each spoken utterance from input speech into a corresponding formal utterance, and mapping each formal utterance into a stylistically formatted written utterance.
摘要翻译： 提供了将语音转换为书面语音的技术。 这些技术包括通过语音识别来转录输入语音，将来自输入语音的每个讲话话语映射成对应的形式发音，并将每个正式话语映射成风格格式化的书写话语。
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