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51. 发明申请

US20050149325A1 Method of noise reduction using correction and scaling vectors with partitioning of the acoustic space in the domain of noisy speech 有权
标题翻译：使用校正和缩放矢量进行噪声降低的方法，其中噪声语音领域的声学空间分割
公开(公告)号：US20050149325A1
公开(公告)日：2005-07-07
申请号：US11059036
申请日：2005-02-16
申请人： Li Deng , Xuedong Huang , Alejandro Acero
发明人： Li Deng , Xuedong Huang , Alejandro Acero
IPC分类号： G10L15/20 , G10L21/02 , G10L21/00
CPC分类号： G10L21/0208
摘要： A method and apparatus are provided for reducing noise in a training signal and/or test signal. The noise reduction technique uses a stereo signal formed of two channel signals, each channel containing the same pattern signal. One of the channel signals is “clean” and the other includes additive noise. Using feature vectors from these channel signals, a collection of noise correction and scaling vectors is determined. When a feature vector of a noisy pattern signal is later received, it is multiplied by the best scaling vector for that feature vector and the best correction vector is added to the product to produce a noise reduced feature vector. Under one embodiment, the best scaling and correction vectors are identified by choosing an optimal mixture component for the noisy feature vector. The optimal mixture component being selected based on a distribution of noisy channel feature vectors associated with each mixture component.
摘要翻译：提供了一种用于减少训练信号和/或测试信号中的噪声的方法和装置。噪声降低技术使用由两个信道信号形成的立体声信号，每个信道包含相同的模式信号。一个通道信号是“干净的”，另一个包括加性噪声。使用来自这些信道信号的特征向量，确定噪声校正和缩放向量的集合。当稍后接收到噪声模式信号的特征向量时，将其乘以该特征向量的最佳缩放向量，并将最佳校正向量加到乘积以产生降噪特征向量。在一个实施例中，通过为噪声特征向量选择最佳混合分量来识别最佳缩放和校正矢量。基于与每个混合物组分相关联的噪声通道特征向量的分布来选择最佳混合物组分。

52. 发明申请

US20050080611A1 Use of a unified language model 失效
公开(公告)号：US20050080611A1
公开(公告)日：2005-04-14
申请号：US11003089
申请日：2004-12-03
申请人： Xuedong Huang , Milind Mahajan , Ye-Yi Wang , Xiaolong Mou
发明人： Xuedong Huang , Milind Mahajan , Ye-Yi Wang , Xiaolong Mou
IPC分类号： G10L15/18 , G06F17/28
CPC分类号： G10L15/193 , G10L15/197
摘要： A language processing system includes a unified language model. The unified language model comprises a plurality of context-free grammars having non-terminal tokens representing semantic or syntactic concepts and terminals, and an N-gram language model having non-terminal tokens. A language processing module capable of receiving an input signal indicative of language accesses the unified language model to recognize the language. The language processing module generates hypotheses for the received language as a function of words of the unified language model and/or provides an output signal indicative of the language and at least some of the semantic or syntactic concepts contained therein.

53. 发明申请

US20050027515A1 Multi-sensory speech detection system 失效
标题翻译：多感官语音检测系统
公开(公告)号：US20050027515A1
公开(公告)日：2005-02-03
申请号：US10629278
申请日：2003-07-29
申请人： Xuedong Huang , Zicheng Liu , Zhengyou Zhang , Michael Sinclair , Alejandro Acero
发明人： Xuedong Huang , Zicheng Liu , Zhengyou Zhang , Michael Sinclair , Alejandro Acero
IPC分类号： G10L11/02 , G10L15/20 , G10L15/24 , H04R1/10 , H04R1/14 , H04R25/00 , G10L11/06
CPC分类号： H04R1/10 , G10L15/20 , G10L15/24 , G10L25/78 , H04R1/14 , H04R25/606
摘要： The present invention combines a conventional audio microphone with an additional speech sensor that provides a speech sensor signal based on an input. The speech sensor signal is generated based on an action undertaken by a speaker during speech, such as facial movement, bone vibration, throat vibration, throat impedance changes, etc. A speech detector component receives an input from the speech sensor and outputs a speech detection signal indicative of whether a user is speaking. The speech detector generates the speech detection signal based on the microphone signal and the speech sensor signal.
摘要翻译：本发明将常规音频麦克风与基于输入提供语音传感器信号的附加话音传感器组合。语音传感器信号基于语音中的扬声器在诸如面部运动，骨骼振动，喉部振动，喉部阻抗变化等中的动作而产生。语音检测器组件从语音传感器接收输入并输出语音检测指示用户是否正在说话的信号。语音检测器基于麦克风信号和语音传感器信号产生语音检测信号。

54. 发明授权

US06654733B1 Fuzzy keyboard 有权
标题翻译：模糊键盘
公开(公告)号：US06654733B1
公开(公告)日：2003-11-25
申请号：US09484095
申请日：2000-01-18
申请人： Joshua Goodman , Daniel Venolia , Xuedong Huang
发明人： Joshua Goodman , Daniel Venolia , Xuedong Huang
IPC分类号： G06F944
CPC分类号： G06F3/04886 , G06F3/0237
摘要： Fuzzy keyboards, to determine a most-likely-to-be-intended keystroke or keystrokes, are disclosed. In one embodiment, a method adds each of one or more keys to each of a current list of key sequence hypotheses, to create a new list of key sequence hypotheses. The method determines a likelihood probability for each hypothesis in the new list, and removes any hypothesis failing to satisfy any of one or more thresholds. The most likely key sequence of the new list may then be displayed. Some embodiments of the invention relate specifically to soft keyboards, while other embodiments relate specifically to real, physical and hard keyboards.
摘要翻译：公开了模糊键盘，以确定最可能被预期的击键或击键。在一个实施例中，一种方法将一个或多个密钥中的每一个添加到密钥序列假设的当前列表中的每一个，以创建密钥序列假设的新列表。该方法确定新列表中每个假设的似然概率，并且去除不能满足一个或多个阈值中的任何一个的假设。然后可以显示新列表的最可能的键序列。本发明的一些实施例具体涉及软键盘，而其他实施例具体涉及实际，物理和硬盘键盘。

55. 发明授权

US5794197A Senone tree representation and evaluation 失效
标题翻译： Senone树代表和评估
公开(公告)号：US5794197A
公开(公告)日：1998-08-11
申请号：US850061
申请日：1997-05-02
申请人： Fileno A. Alleva , Xuedong Huang , Mei-Yuh Hwang
发明人： Fileno A. Alleva , Xuedong Huang , Mei-Yuh Hwang
IPC分类号： G10L15/02 , G10L15/06 , G10L15/14 , G10L15/18 , G10L5/06
CPC分类号： G10L15/146 , G10L15/187 , G10L2015/0631
摘要： A speech recognition method provides improved modeling in recognition accuracy using hidden Markov models. During training, the method creates a senone tree for each state of each phoneme encountered in a data set of training words. All output distributions received for a selected state of a selected phoneme in the set of training words are clustered together in a root node of a senone tree. Each node of the tree beginning with the root node is divided into two nodes by asking linguistic questions regarding the phonemes immediately to the left and right of a central phoneme of a triphone. At a predetermined point, the tree creation stops, resulting in leaves representing clustered output distributions known as senones. The senone trees allow all possible triphones to be mapped into a sequence of senones simply by traversing the senone trees associated with the central phoneme of the triphone. As a result, unseen triphones not encountered in the training data can be modeled with senones created using the triphones actually found in the training data.
摘要翻译：语音识别方法使用隐马尔可夫模型提供了识别精度的改进建模。在训练期间，该方法为训练词数据集中遇到的每个音素的每个状态创建一个声调树。在训练词集合中为选定音素的选定状态接收的所有输出分布被聚集在声调树的根节点中。从根节点开始的树的每个节点被分成两个节点，通过询问关于三音节的中心音素的左侧和右侧的音素的语言问题。在预定的点，树的创建停止，导致代表聚集的输出分布的叶被称为senones。声音树允许所有可能的三通电话通过遍历与三通电话的中心音素相关联的音素树来映射成一系列的单音。因此，训练数据中未见到的看不见的三重奏可以使用在训练数据中实际发现的三通奏音而创建的声音进行建模。

56. 发明授权

US10606989B2 Computational systems and methods for verifying personal information during transactions 有权
公开(公告)号：US10606989B2
公开(公告)日：2020-03-31
申请号：US13374528
申请日：2011-12-30
申请人： Marc E. Davis , Matthew G. Dyor , William Gates , Xuedong Huang , Roderick A. Hyde , Edward K. Y. Jung , Jordin T. Kare , Royce A. Levien , Richard T. Lord , Robert W. Lord , Qi Lu , Mark A. Malamud , Nathan P. Myhrvold , Satya Nadella , Daniel Reed , Harry Shum , Clarence T. Tegreene , Lowell L. Wood, Jr.
发明人： Marc E. Davis , Matthew G. Dyor , William Gates , Xuedong Huang , Roderick A. Hyde , Edward K. Y. Jung , Jordin T. Kare , Royce A. Levien , Richard T. Lord , Robert W. Lord , Qi Lu , Mark A. Malamud , Nathan P. Myhrvold , Satya Nadella , Daniel Reed , Harry Shum , Clarence T. Tegreene , Lowell L. Wood, Jr.
IPC分类号： G06F21/31 , G06Q20/32 , G06Q20/40 , H04L29/06
摘要： Methods, apparatuses, computer program products, devices and systems are described that carry out accessing at least one persona that includes a unique identifier that is at least partly based on a first user's device-identifier data and the first user's network-participation data; verifying the persona by comparing the first user's device-identifier data and the first user's network-participation data of the unique identifier to a second user's device-identifier data and the second user's network-participation data; and presenting the persona in response to a request for personal information.

57. 发明授权

US09928485B2 Computational systems and methods for regulating information flow during interactions 有权
公开(公告)号：US09928485B2
公开(公告)日：2018-03-27
申请号：US13373542
申请日：2011-11-16
申请人： Marc E. Davis , Matthew G. Dyor , William Gates , Xuedong Huang , Roderick A. Hyde , Edward K. Y. Jung , Jordin T. Kare , Royce A. Levien , Richard T. Lord , Robert W. Lord , Qi Lu , Mark A. Malamud , Nathan P. Myhrvold , Satya Nadella , Daniel Reed , Harry Shum , Clarence T. Tegreene , Lowell L. Wood, Jr.
发明人： Marc E. Davis , Matthew G. Dyor , William Gates , Xuedong Huang , Roderick A. Hyde , Edward K. Y. Jung , Jordin T. Kare , Royce A. Levien , Richard T. Lord , Robert W. Lord , Qi Lu , Mark A. Malamud , Nathan P. Myhrvold , Satya Nadella , Daniel Reed , Harry Shum , Clarence T. Tegreene , Lowell L. Wood, Jr.
IPC分类号： G06F15/16 , G06Q10/10 , G06Q30/08
CPC分类号： G06Q10/10 , G06Q30/08
摘要： Methods, apparatuses, computer program products, devices and systems are described that carry out accepting at least one indication of an interaction involving at least one member of a network; creating a persona corresponding to the at least one member of a network, wherein the persona is at least partly based on the indication of an interaction; and presenting the persona for use in the interaction involving the at least one member of the network.

58. 发明授权

US09501759B2 Search query and document-related data translation 有权
标题翻译：搜索查询和文档相关的数据翻译
公开(公告)号：US09501759B2
公开(公告)日：2016-11-22
申请号：US13328924
申请日：2011-12-16
申请人： Jianfeng Gao , Xuedong Huang , Mei Li , Zhenghao Wang , Christopher John Brockett , William B. Dolan
发明人： Jianfeng Gao , Xuedong Huang , Mei Li , Zhenghao Wang , Christopher John Brockett , William B. Dolan
IPC分类号： G06F17/30 , G06F7/00 , G06Q10/10 , G06Q30/02
CPC分类号： G06Q10/10 , G06F17/30687 , G06Q30/0241
摘要： The subject disclosure is directed towards developing a translation model for mapping search query terms to document-related data. By processing user logs comprising search histories into word-aligned query-document pairs, the translation model may be trained using data, such as probabilities, corresponding to the word-aligned query-document pairs. After incorporating the translation model into model data for a search engine, the translation model is used may used as features for producing relevance scores for current search queries and ranking documents/advertisements according to relevance.
摘要翻译：本发明旨在开发用于将搜索查询词语映射到文档相关数据的翻译模型。通过将包括搜索历史的用户日志处理成字对齐的查询 - 文档对，可以使用对应于字对齐的查询 - 文档对的诸如概率的数据来训练翻译模型。在将翻译模型合并到搜索引擎的模型数据中之后，使用翻译模型可以用作根据相关性产生当前搜索查询和排序文档/广告的相关性分数的特征。

59. 发明授权

US09183520B2 Computational systems and methods for linking users of devices 有权
标题翻译：用于连接设备用户的计算系统和方法
公开(公告)号：US09183520B2
公开(公告)日：2015-11-10
申请号：US13199829
申请日：2011-09-09
申请人： Marc E. Davis , Matthew G. Dyor , William Gates , Xuedong Huang , Roderick A. Hyde , Edward K. Y. Jung , Royce A. Levien , Richard T. Lord , Robert W. Lord , Qi Lu , Mark A. Malamud , Nathan P. Myhrvold , Satya Nadella , Daniel Reed , Harry Shum , Clarence T. Tegreene , Lowell L. Wood, Jr.
发明人： Marc E. Davis , Matthew G. Dyor , William Gates , Xuedong Huang , Roderick A. Hyde , Edward K. Y. Jung , Royce A. Levien , Richard T. Lord , Robert W. Lord , Qi Lu , Mark A. Malamud , Nathan P. Myhrvold , Satya Nadella , Daniel Reed , Harry Shum , Clarence T. Tegreene , Lowell L. Wood, Jr.
IPC分类号： G06F15/16 , G06Q10/06 , G06Q10/10 , G06Q40/00 , G06Q50/00 , G06Q50/30
CPC分类号： G06Q10/06 , G06Q10/107 , G06Q40/00 , G06Q50/01 , G06Q50/30
摘要： Methods, apparatuses, computer program products, devices and systems are described that carry out accepting device-identifier data corresponding to at least one communication device; accepting network-participation identifier data associated with a verified real-world user associated with the at least one communication device; and assigning a unique identifier at least partly based on the device-identifier data and the network-participation identifier data.
摘要翻译：描述了执行与至少一个通信设备相对应的接收设备标识符数据的方法，设备，计算机程序产品，设备和系统; 接受与所述至少一个通信设备相关联的经验证的真实世界用户相关联的网络参与标识符数据; 以及至少部分地基于所述设备标识符数据和所述网络参与标识符数据来分配唯一标识符。

60. 发明授权

US09025587B2 Auto answer in voice over internet protocol 有权
标题翻译：通过互联网协议自动应答
公开(公告)号：US09025587B2
公开(公告)日：2015-05-05
申请号：US11504924
申请日：2006-08-16
申请人： Kuansan Wang , Xuedong Huang
发明人： Kuansan Wang , Xuedong Huang
IPC分类号： H04L12/66 , H04L29/06 , H04L12/28 , H04L12/56 , H04J3/16 , H04J3/22 , H04M1/253
CPC分类号： H04L65/4061 , H04L65/1006 , H04L65/1069 , H04L65/1083 , H04M1/2535
摘要： An auto-answer feature is implemented in SIP by configuring a receiving device to automatically acknowledge and answer an incoming call or session from a specific trusted third party. The receiving device may skip to an OK response to an INVITE request when the call is routed through the trusted third party. When the device can automatically answer the incoming call, advanced features such as Push To Talk, Information Tone, Click to Call, and Remote Monitoring may be easily implemented.
摘要翻译：通过配置接收设备来自动确认和应答来自特定可信第三方的呼入或会话，在SIP中实现自动应答功能。当呼叫通过受信任的第三方路由时，接收设备可跳过对INVITE请求的OK响应。当设备可以自动接听来电时，可以轻松实现诸如即按即说，信息音，点击通话和远程监控等高级功能。

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