On-demand language translation for television programs
    31.
    发明授权
    On-demand language translation for television programs 有权
    电视节目的按需语言翻译

    公开(公告)号:US07809549B1

    公开(公告)日:2010-10-05

    申请号:US11424330

    申请日:2006-06-15

    IPC分类号: G06F17/28

    CPC分类号: G06F17/289

    摘要: In an embodiment, a method of providing an on demand translation service is provided. A subscriber may be charged a reduced fee or no fee for use of the on demand translation service in exchange for displaying commercial messages to the subscriber, the commercial messages being selected based on subscriber information. A multimedia signal including information in a source language may be received. The information may be obtained as text in the source language from the multimedia signal. The text may be translated from the source language to a target language. Translated information, based on the translated text, may be transmitted to a processing device for presentation to the subscriber. The received multimedia signal may be sent to a multimedia device for viewing.

    摘要翻译: 在一个实施例中,提供了提供按需翻译服务的方法。 用户可能被收取减少的费用或不使用按需翻译服务的费用,以便向用户显示商业消息,基于用户信息选​​择商业消息。 可以接收包括源语言的信息的多媒体信号。 可以从多媒体信号中获取源语言中的文本信息。 文本可以从源语言翻译成目标语言。 基于翻译的文本的翻译信息可以被发送到处理设备以呈现给订阅者。 所接收的多媒体信号可以被发送到多媒体设备以供观看。

    SYSTEM AND METHOD FOR REFERRING TO ENTITIES IN A DISCOURSE DOMAIN
    32.
    发明申请
    SYSTEM AND METHOD FOR REFERRING TO ENTITIES IN A DISCOURSE DOMAIN 有权
    引导领域实体的系统和方法

    公开(公告)号:US20100153105A1

    公开(公告)日:2010-06-17

    申请号:US12333863

    申请日:2008-12-12

    IPC分类号: G10L15/26

    摘要: Disclosed herein are systems, computer-implemented methods, and tangible computer-readable media for referring to entities. The method includes receiving domain-specific training data of sentences describing a target entity in a context, extracting a speaker history and a visual context from the training data, selecting attributes of the target entity based on at least one of the speaker history, the visual context, and speaker preferences, generating a text expression referring to the target entity based on at least one of the selected attributes, the speaker history, and the context, and outputting the generated text expression. The weighted finite-state automaton can represent partial orderings of word pairs in the domain-specific training data. The weighted finite-state automaton can be speaker specific or speaker independent. The weighted finite-state automaton can include a set of weighted partial orderings of the training data for each possible realization.

    摘要翻译: 本文公开了用于引用实体的系统,计算机实现的方法和有形的计算机可读介质。 该方法包括接收在上下文中描述目标实体的句子的特定领域的训练数据,从训练数据中提取讲者历史和视觉上下文,基于说话者的历史,视觉上的至少一个来选择目标实体的属性 上下文和说话人首选项,基于所选择的属性,说话者历史和上下文中的至少一个生成参考目标实体的文本表达,并输出所生成的文本表达。 加权有限状态自动机可以表示域特定训练数据中单词对的部分排序。 加权有限状态自动机可以是扬声器专用或扬声器独立的。 加权有限状态自动机可以包括用于每个可能实现的训练数据的一组加权部分排序。

    On-demand language translation for television programs
    33.
    发明授权
    On-demand language translation for television programs 有权
    电视节目的按需语言翻译

    公开(公告)号:US07711543B2

    公开(公告)日:2010-05-04

    申请号:US11279852

    申请日:2006-04-14

    IPC分类号: G06F17/28

    摘要: A method, a system and a machine-readable medium are provided for an on demand translation service. A translation module including at least one language pair module for translating a source language to a target language may be made available for use by a subscriber. The subscriber may be charged a fee for use of the requested on demand translation service or may be provided use of the on demand translation service for free in exchange for displaying commercial messages to the subscriber. A video signal may be received including information in the source language, which may be obtained as text from the video signal and may be translated from the source language to the target language by use of the translation module. Translated information, based on the translated text, may be added into the received video signal. The video signal including the translated information in the target language may be sent to a display device.

    摘要翻译: 为按需翻译服务提供方法,系统和机器可读介质。 包括用于将源语言翻译成目标语言的至少一个语言对模块的翻译模块可以被用户使用。 用户可能会收取使用所请求的按需翻译服务的费用,或者可以免费使用按需翻译服务,以便向用户显示商业消息。 可以接收包括源语言的信息的视频信号,其可以从视频信号获取为文本,并且可以通过使用翻译模块从源语言翻译成目标语言。 基于翻译文本的翻译信息可以被添加到接收的视频信号中。 可以将包括目标语言的翻译信息的视频信号发送到显示装置。

    Automatic learning for mapping spoken/text descriptions of products onto available products
    34.
    发明授权
    Automatic learning for mapping spoken/text descriptions of products onto available products 失效
    自动学习将产品的口语/文字描述映射到可用产品上

    公开(公告)号:US07630917B2

    公开(公告)日:2009-12-08

    申请号:US11279802

    申请日:2006-04-14

    IPC分类号: G06F17/30 G06Q10/00

    摘要: A method, processing device, and machine-readable medium are provided. Costs of states of a state space are calculated. Each state represent one or more available product attributes having zero or more decided attribute values. The calculating is based, at least in part, on training data associated with previously requested and offered products. determining a next state such that one or more products are available and a sum of values, including a cost of a next state and a cost of a perturbation of one of the one or more requested product attribute values to reach the next state is a minimum value. A value for a product attribute is mapped according to the minimum sum of values and product attribute values of available products.

    摘要翻译: 提供了一种方法,处理装置和机器可读介质。 计算状态空间的状态成本。 每个状态表示具有零个或多个决定的属性值的一个或多个可用的产品属性。 该计算至少部分地基于与先前请求和提供的产品相关联的训练数据。 确定下一状态使得一个或多个产品可用,并且包括下一个状态的成本和一个或多个所请求的产品属性值中的一个的扰动成本达到下一个状态的值的总和是最小的 值。 产品属性的值根据可用产品的值和产品属性值的最小总和进行映射。

    Discriminative training of models for sequence classification
    37.
    发明申请
    Discriminative training of models for sequence classification 审中-公开
    序列分类模型的辨别性训练

    公开(公告)号:US20080162117A1

    公开(公告)日:2008-07-03

    申请号:US11646983

    申请日:2006-12-28

    IPC分类号: G06F17/21

    CPC分类号: G06F17/2818

    摘要: Classification of sequences, such as the translation of natural language sentences, is carried out using an independence assumption. The independence assumption is an assumption that the probability of a correct translation of a source sentence word into a particular target sentence word is independent of the translation of other words in the sentence. Although this assumption is not a correct one, a high level of word translation accuracy is nonetheless achieved. In particular, discriminative training is used to develop models for each target vocabulary word based on a set of features of the corresponding source word in training sentences, with at least one of those features relating to the context of the source word. Each model comprises a weight vector for the corresponding target vocabulary word. The weights comprising the vectors are associated with respective ones of the features; each weight is a measure of the extent to which the presence of that feature for the source word makes it more probable that the target word in question is the correct one.

    摘要翻译: 使用独立假设进行序列分类,如自然语言句子的翻译。 独立性假设是将源语句正确翻译成特定目标句子词的概率与句子中其他单词的翻译无关的假设。 尽管这种假设不是正确的,但仍然会实现高水平的字翻译精度。 特别地,歧视性训练被用于基于训练句子中相应源词的一组特征来开发每个目标词汇词的模型,其中至少一个与源词的上下文有关的特征。 每个模型包括对应的目标词汇单词的权重向量。 包括向量的权重与相应的特征相关联; 每个权重是衡量源字符的该特征的存在程度使得所述目标词更可能是正确的。

    System and method for natural language generation
    39.
    发明授权
    System and method for natural language generation 有权
    自然语言生成的系统和方法

    公开(公告)号:US07231341B2

    公开(公告)日:2007-06-12

    申请号:US11195973

    申请日:2005-08-03

    IPC分类号: G06F17/20

    CPC分类号: G06F17/271 G06F17/2881

    摘要: A system, method and computer-readable medium for generating natural language utilizes a stochastic process to choose a derivation tree according to a predetermined grammar, such as tree-adjoined grammar (TAG). A word lattice is created from a single semi-specified derivation tree and the proper path (i.e., desired output string) is selected from the lattice using a least cost, or other appropriate algorithms.

    摘要翻译: 用于生成自然语言的系统,方法和计算机可读介质利用随机过程根据诸如树相邻语法(TAG)的预定语法来选择导出树。 从单个半指定的导出树创建一个字格,并且使用最小成本或其他适当的算法从网格中选择适当的路径(即期望的输出串)。

    System and method for learning latent representations for natural language tasks
    40.
    发明授权
    System and method for learning latent representations for natural language tasks 有权
    学习自然语言任务的潜在表征的系统和方法

    公开(公告)号:US09135241B2

    公开(公告)日:2015-09-15

    申请号:US12963126

    申请日:2010-12-08

    IPC分类号: G06F17/28

    CPC分类号: G06F17/28

    摘要: Disclosed herein are systems, methods, and non-transitory computer-readable storage media for learning latent representations for natural language tasks. A system configured to practice the method analyzes, for a first natural language processing task, a first natural language corpus to generate a latent representation for words in the first corpus. Then the system analyzes, for a second natural language processing task, a second natural language corpus having a target word, and predicts a label for the target word based on the latent representation. In one variation, the target word is one or more word such as a rare word and/or a word not encountered in the first natural language corpus. The system can optionally assigning the label to the target word. The system can operate according to a connectionist model that includes a learnable linear mapping that maps each word in the first corpus to a low dimensional latent space.

    摘要翻译: 本文公开了用于学习自然语言任务的潜在表示的系统,方法和非暂时的计算机可读存储介质。 一种被配置为练习该方法的系统,分析第一自然语言处理任务中的第一自然语言语料库以产生第一语料库中的单词的潜在表示。 然后,系统针对第二自然语言处理任务分析具有目标词的第二自然语言语料库,并且基于潜在表示来预测目标词的标签。 在一个变体中,目标词是一个或多个单词,例如在第一自然语言语料库中不遇到的罕见单词和/或单词。 系统可以选择将标签分配给目标字。 该系统可以根据连接主义模型来操作,该连接主义模型包括将第一语料库中的每个单词映射到低维空间的可学习的线性映射。