Intelligent Dialogue Amongst Competitive User Applications
    4.
    发明申请
    Intelligent Dialogue Amongst Competitive User Applications 有权
    竞争用户应用之间的智能对话

    公开(公告)号:US20130198761A1

    公开(公告)日:2013-08-01

    申请号:US13363727

    申请日:2012-02-01

    IPC分类号: G06F9/54

    CPC分类号: G06Q30/0281

    摘要: A method, an apparatus and an article of manufacture for enabling communication between at least two computer applications that is observable to a user. The method includes obtaining a description of functions for each of the at least two computer applications, comparing the description of functions for each of the at least two computer applications, generating a dialog between the at least two applications based on the comparing of the description of functions for each of the at least two computer applications, and making the dialog available to a user.

    摘要翻译: 一种用于实现可被用户观察的至少两个计算机应用之间的通信的方法,装置和制品。 所述方法包括获得所述至少两个计算机应用中的每一个的功能的描述,比较所述至少两个计算机应用中的每一个的功能的描述,基于所述至少两个计算机应用的描述的比较来生成所述至少两个应用之间的对话 对于至少两个计算机应用程序中的每一个应用程序的功能,以及使对话可用于用户。

    Intelligent dialogue amongst competitive user applications
    6.
    发明授权
    Intelligent dialogue amongst competitive user applications 有权
    竞争激烈的用户应用之间的智能对话

    公开(公告)号:US08825533B2

    公开(公告)日:2014-09-02

    申请号:US13363727

    申请日:2012-02-01

    IPC分类号: G06Q30/00

    CPC分类号: G06Q30/0281

    摘要: A method, an apparatus and an article of manufacture for enabling communication between at least two computer applications that is observable to a user. The method includes obtaining a description of functions for each of the at least two computer applications, comparing the description of functions for each of the at least two computer applications, generating a dialog between the at least two applications based on the comparing of the description of functions for each of the at least two computer applications, and making the dialog available to a user.

    摘要翻译: 一种用于实现可被用户观察的至少两个计算机应用之间的通信的方法,装置和制品。 所述方法包括获得所述至少两个计算机应用中的每一个的功能的描述,比较所述至少两个计算机应用中的每一个的功能的描述,基于所述至少两个计算机应用的描述的比较来生成所述至少两个应用之间的对话 对于至少两个计算机应用程序中的每一个应用程序的功能,以及使对话可用于用户。

    Phonetic features for speech recognition
    7.
    发明授权
    Phonetic features for speech recognition 有权
    用于语音识别的语音特征

    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

    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。

    Phonetic Features for Speech Recognition
    8.
    发明申请
    Phonetic Features for Speech Recognition 有权
    语音识别的语音特征

    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

    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。

    DIRECTIONAL OPTIMIZATION VIA EBW
    9.
    发明申请
    DIRECTIONAL OPTIMIZATION VIA EBW 有权
    通过EBW进行方向优化

    公开(公告)号:US20110282925A1

    公开(公告)日:2011-11-17

    申请号:US12777768

    申请日:2010-05-11

    IPC分类号: G06F1/02 G06F17/11

    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。

    Directional optimization via EBW
    10.
    发明授权
    Directional optimization via EBW 有权
    通过EBW定向优化

    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。