会员体验
专利管家(专利管理)
工作空间(专利管理)
风险监控(情报监控)
数据分析(专利分析)
侵权分析(诉讼无效)
联系我们
交流群
官方交流:
QQ群: 891211   
微信请扫码    >>>
现在联系顾问~
热词
    • 4. 发明授权
    • VoIP variable metadata
    • VoIP变量元数据
    • US08842660B2
    • 2014-09-23
    • US11394578
    • 2006-03-31
    • David MilsteinDavid A HowellLinda CriddleMichael D MaluegPhilip Andrew Chou
    • David MilsteinDavid A HowellLinda CriddleMichael D MaluegPhilip Andrew Chou
    • H04L12/66H04M1/56H04M15/06H04M1/57H04M3/42
    • H04M1/571H04L12/66H04M1/575H04M3/42025
    • A method and system for communicating a variable set of contextual information relating to a conversation over a communication channel is provided. When the contextual information is exchanged, any authorized sending party of the contextual information can change the scope, content, or amount of the contextual information that is transmitted to a next receiving party in a determined communication channel path. Before transmitting the contextual information, a desirable scope of the contextual information may be determined based on the next receiving party, in conjunction with the sending party's rules. The contextual information may be updated by adding new contextual information and/or deleting part of the contextual information which is outside of the scope. No contextual information may be transmitted if the next destination desires no contextual information or does not have capabilities to receive any contextual information.
    • 提供了一种用于在通信信道上传送与会话相关的可变的上下文信息集合的方法和系统。 当上下文信息被交换时,上下文信息的任何授权的发送方可以改变在确定的通信信道路径中发送给下一个接收方的上下文信息的范围,内容或量。 在发送上下文信息之前,可以结合发送方的规则,基于下一个接收方来确定上下文信息的期望范围。 可以通过添加新的上下文信息和/或删除在范围之外的上下文信息的一部分来更新上下文信息。 如果下一个目的地不需要上下文信息或者不具有接收任何上下文信息的能力,则不会发送上下文信息。
    • 5. 发明授权
    • Method for aligning a text image to a transcription of the image
    • 将文本图像与图像转录对齐的方法
    • US5689585A
    • 1997-11-18
    • US431004
    • 1995-04-28
    • Dan S. BloombergLeslie T. NilesGary E. KopecPhilip Andrew Chou
    • Dan S. BloombergLeslie T. NilesGary E. KopecPhilip Andrew Chou
    • G06K9/20G06K9/72
    • G06K9/00469G06K9/72G06K2209/01
    • A method for establishing a relationship between a text image and a transcription associated with the text image uses conventional image processing techniques to identify one or more geometric attributes, or image parameters, of each of a sequence of regions of the text image. The transcription labels in the transcription are analyzed to determine a comparable set of parameters in transcription label sequence. A matching operation then matches the respective parameters of the two sequences to identify image regions that match with transcription regions. The result is an output data structure that minimally identifies image locations of interest to a subsequent operation that processes the text image. The output data structure may also pair each of the image locations of interest to a transcription location, in effect producing a set of labeled image locations. In one embodiment, the sequence of locations of words and their observed lengths in the text image are determined. The transcription is analyzed to identify words, and transcription word lengths are computed using an estimated image character width of glyphs in the text image. The sequence of observed image word lengths is then matched to the sequence of computed transcription word lengths using a dynamic programming algorithm that finds a best path through a two-dimensional lattice of nodes and transitions between nodes, where the transitions represent pairs of sequences of zero or more word lengths. An output data structure contains entries, each of which pairs a transcription word with a matching image word location.
    • 用于建立文本图像与与文本图像相关联的转录之间的关系的方法使用常规图像处理技术来识别文本图像的区域序列中的每一个的一个或多个几何属性或图像参数。 分析转录中的转录标记以确定转录标记序列中可比较的一组参数。 匹配操作然后匹配两个序列的相应参数以识别与转录区域匹配的图像区域。 结果是输出数据结构,其最小程度地识别处理文本图像的后续操作感兴趣的图像位置。 输出数据结构还可以将感兴趣的每个图像位置配对到转录位置,实际上产生一组标记的图像位置。 在一个实施例中,确定单词的位置序列及其在文本图像中的观察长度。 分析转录以识别词,并且使用文本图像中的字形的估计图像字符宽度来计算转录词长度。 然后使用动态规划算法将观察到的图像字长度的序列与计算出的转录词长度的序列匹配,该动态规划算法通过节点的二维网格和节点之间的转换找到最佳路径,其中,转换代表零序列对 或更多字长。 输出数据结构包含条目,每个条目将转录词与匹配的图像字位置配对。
    • 6. 发明授权
    • Speech separation with microphone arrays
    • 麦克风阵列语音分离
    • US08144896B2
    • 2012-03-27
    • US12035439
    • 2008-02-22
    • Zicheng LiuPhilip Andrew ChouJacek Dmochowski
    • Zicheng LiuPhilip Andrew ChouJacek Dmochowski
    • H04B15/00
    • H04R27/00G10L21/0272
    • A system that facilitates blind source separation in a distributed microphone meeting environment for improved teleconferencing. Input sensor (e.g., microphone) signals are transformed to the frequency-domain and independent component analysis is applied to compute estimates of frequency-domain processing matrices. Modified permutations of the processing matrices are obtained based upon a maximum magnitude based de-permutation scheme. Estimates of the plurality of source signals are provided based upon the modified frequency-domain processing matrices and input sensor signals.Optionally, segments during which the set of active sources is a subset of the set of all sources can be exploited to compute more accurate estimates of frequency-domain mixing matrices. Source activity detection can be applied to determine which speaker(s), if any, are active. Thereafter, a least squares post-processing of the frequency-domain independent components analysis outputs can be employed to adjust the estimates of the source signals based on source inactivity.
    • 一种促进分布式麦克风会议环境中盲源分离的系统,用于改进电话会议。 输入传感器(例如麦克风)信号被变换到频域,并且应用独立分量分析来计算频域处理矩阵的估计。 基于最大幅度的去排列方案获得处理矩阵的修改排列。 基于改进的频域处理矩阵和输入传感器信号来提供多个源信号的估计。 可选地,可以利用其中该组活动源是所有源的集合的子集的段来计算频域混合矩阵的更准确的估计。 源活动检测可以应用于确定哪些扬声器(如果有)是活动的。 此后,可以采用频域独立分量分析输出的最小二乘后处理,以基于源不活动来调整源信号的估计。
    • 7. 发明授权
    • Models for routing tree selection in peer-to-peer communications
    • 在对等通信中路由树选择的模型
    • US07738406B2
    • 2010-06-15
    • US12247431
    • 2008-10-08
    • Shao LiuSudipta SenguptaMung ChiangJin LiPhilip Andrew Chou
    • Shao LiuSudipta SenguptaMung ChiangJin LiPhilip Andrew Chou
    • H04L12/28
    • H04L45/00H04L45/48
    • Peer-to-peer communications sessions involve the transmission of one or more data streams from a source to a set of receivers that may redistribute portions of the data stream via a set of routing trees. Achieving a comparatively high, sustainable data rate throughput of the data stream(s) may be difficult due to the large number of available routing trees, as well as pertinent variations in the nature of the communications session (e.g., upload communications caps, network link caps, the presence or absence of helpers, and the full or partial interconnectedness of the network.) The selection of routing trees may be facilitated through the representation of the node set according to a linear programming model, such as a primal model or a linear programming dual model, and iterative processes for applying such models and identifying low-cost routing trees during an iteration.
    • 对等通信会话涉及将一个或多个数据流从源传输到可以通过一组路由树重新分配数据流的部分的一组接收机。 由于大量的可用路由树以及通信会话性质的相关变化(例如,上传通信上限,网络链路),实现数据流的相对较高,可持续的数据速率吞吐量可能是困难的 帽子,帮助者的存在或不存在以及网络的全部或部分互连性)。可以通过根据线性规划模型(例如原始模型或线性的)的节点集合的表示来促进路由树的选择 编程双重模型,以及迭代过程,用于应用此类模型,并在迭代期间识别低成本路由树。
    • 8. 发明申请
    • MODELS FOR ROUTING TREE SELECTION IN PEER-TO-PEER COMMUNICATIONS
    • 在对等通信中选择树的选择模式
    • US20100085979A1
    • 2010-04-08
    • US12247431
    • 2008-10-08
    • Shao LiuSudipta SenguptaMung ChiangJin LiPhilip Andrew Chou
    • Shao LiuSudipta SenguptaMung ChiangJin LiPhilip Andrew Chou
    • H04L12/56
    • H04L45/00H04L45/48
    • Peer-to-peer communications sessions involve the transmission of one or more data streams from a source to a set of receivers that may redistribute portions of the data stream via a set of routing trees. Achieving a comparatively high, sustainable data rate throughput of the data stream(s) may be difficult due to the large number of available routing trees, as well as pertinent variations in the nature of the communications session (e.g., upload communications caps, network link caps, the presence or absence of helpers, and the full or partial interconnectedness of the network.) The selection of routing trees may be facilitated through the representation of the node set according to a linear programming model, such as a primal model or a linear programming dual model, and iterative processes for applying such models and identifying low-cost routing trees during an iteration.
    • 对等通信会话涉及将一个或多个数据流从源传输到可以通过一组路由树重新分配数据流的部分的一组接收器。 由于大量的可用路由树以及通信会话性质的相关变化(例如,上传通信上限,网络链路),实现数据流的相对较高,可持续的数据速率吞吐量可能是困难的 帽子,帮助者的存在或不存在以及网络的全部或部分互连性)。可以通过根据线性规划模型(例如原始模型或线性的)的节点集合的表示来促进路由树的选择 编程双重模型,以及迭代过程,用于应用此类模型,并在迭代期间识别低成本路由树。
    • 9. 发明授权
    • Layered multiple description coding
    • 分层多重描述编码
    • US07426677B2
    • 2008-09-16
    • US11787387
    • 2007-04-16
    • Philip Andrew ChouVenkata N. PadmanabhanHelen Wang
    • Philip Andrew ChouVenkata N. PadmanabhanHelen Wang
    • H03M13/00
    • H04N21/6405H04N19/39
    • A data sequence may be encoded in a plurality of layers of multiple description coding. The layers of multiple description coding may include a first and a second layer of multiple description coding. The first layer of multiple description coding may include an initial part of a data sequence as well as forward error correction code for the initial part. The second layer of multiple description coding may include a next part of the data sequence as well as forward error correction code for the next part. A first set of data sequence breakpoints may be determined for the first layer of multiple description coding. A second set of data sequence breakpoints may be determined for the second layer. The data sequence may be encoded in the plurality of layers of multiple description coding as a function of the first and second sets of data sequence breakpoints.
    • 数据序列可以被编码在多个多描述编码层中。 多描述编码的层可以包括多描述编码的第一和第二层。 多描述编码的第一层可以包括数据序列的初始部分以及初始部分的前向纠错码。 多重描述编码的第二层可以包括数据序列的下一部分以及下一部分的前向纠错码。 可以为第一层多重描述编码确定第一组数据序列断点。 可以为第二层确定第二组数据序列断点。 数据序列可以在多个描述编码的多个层中作为第一和第二组数据序列断点进行编码。
    • 10. 发明授权
    • Unsupervised training of character templates using unsegmented samples
    • 使用未分段样本的角色模板的无监督训练
    • US5956419A
    • 1999-09-21
    • US430635
    • 1995-04-28
    • Gary E. KopecPhilip Andrew Chou
    • Gary E. KopecPhilip Andrew Chou
    • G06K9/62G06K9/68
    • G06K9/68G06K9/6256
    • A method for operating a machine to perform unsupervised training of a set of character templates uses as the source of training samples an image source of character images, called glyphs, that need not be manually or automatically segmented or isolated prior to training. A recognition operation performed on the image source of character images produces a labeled glyph position data structure that includes, for each glyph in the image source, a glyph image position in the image source associating an estimated image location of the glyph in the image source with a character label paired with the glyph image position that indicates the character in the character set being trained. The labeled glyph position data and the image source are then used to determine sample image regions in the image source; each sample image region is large enough to contain at least a single glyph but need not be restricted in size to only contain a single glyph. The template construction process using unsegmented samples is mathematically modeled as an optimization problem that optimizes a function that represents the set of character templates being trained as an ideal image to be reconstructed to match the input image. The method produces all of the character templates substantially contemporaneously by using a novel pixel scoring technique that implements an approximation of a maximum likelihood criterion subject to a constraint on the templates produced which holds that foreground pixels in adjacently positioned character images have substantially nonoverlapping foreground pixels. The character templates produced may be binary templates or arrays of probability values.
    • 用于操作机器执行一组字符模板的无监督训练的方法用作训练的来源,在训练之前不需要手动地或自动地分割或分离字符图像的称为字形的图像源。 对字符图像的图像源执行的识别操作产生标记的字形位置数据结构,其包括对于图像源中的每个字形,图像源中的字形图像位置将图像源中的字形的估计图像位置与 与字形图像位置配对的字符标签,其指示被训练的字符集中的字符。 然后使用标记的字形位置数据和图像源来确定图像源中的样本图像区域; 每个样本图像区域足够大以至少包含单个字形,但不需要将其限制为仅包含单个字形。 使用未分段样本的模板构建过程在数学上被建模为优化问题,其优化表示被训练为被重建以匹配输入图像的理想图像的字符模板集合的函数。 该方法通过使用新颖的像素评分技术来产生所有的字符模板,该新颖的像素评分技术实现对所产生的模板的约束的最大似然准则的近似,该模板保持相邻位置的字符图像中的前景像素具有基本上不重叠的前景像素。 生成的字符模板可以是二进制模板或概率值数组。