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    • 9. 发明授权
    • System and method for providing speech recognition using personal vocabulary in a network environment
    • 用于在网络环境中使用个人词汇提供语音识别的系统和方法
    • US09201965B1
    • 2015-12-01
    • US12571414
    • 2009-09-30
    • Satish K. GannuGuido JouretAshutosh A. Malegaonkar
    • Satish K. GannuGuido JouretAshutosh A. Malegaonkar
    • G10L15/26G06F17/30
    • G06F17/30867G06F17/30761
    • A method is provided in one example and includes receiving a media file and generating a text file based on the media file. The method includes identifying selected words within the text file based on a whitelist, the whitelist includes a plurality of designated words to be tagged. The selected words are compared to a group of words associated with an individual. One or more of the selected words are removed based on the selected words not being found in the group of words associated with the individual. In more specific embodiments, the method includes generating a resultant after removing one or more of the selected words, the resultant can be separated into fields that identify a title and an author associated with the resultant. At least one of the selected words that is removed is associated with a false positive associated with two words that phonetically sound similar.
    • 在一个示例中提供了一种方法,包括接收媒体文件并基于媒体文件生成文本文件。 该方法包括基于白名单来识别文本文件内的所选择的单词,白名单包括要标记的多个指定单词。 将所选择的单词与与个人相关联的一组单词进行比较。 基于在与个人相关联的单词组中没有找到的所选择的单词来删除一个或多个所选择的单词。 在更具体的实施例中,该方法包括在移除所选择的一个或多个单词之后生成结果,所得到的结果可被分成标识标题的作品和与作品相关联的作者。 所删除的所选择的单词中的至少一个与与语音相似的两个单词相关联的假阳性相关联。
    • 10. 发明授权
    • System and method for generating personal vocabulary from network data
    • 用于从网络数据生成个人词汇的系统和方法
    • US08990083B1
    • 2015-03-24
    • US12571404
    • 2009-09-30
    • Satish K. GannuAshutosh A. MalegaonkarVirgil N. Mihailovici
    • Satish K. GannuAshutosh A. MalegaonkarVirgil N. Mihailovici
    • G10L15/00
    • G10L15/06G10L2015/0633
    • A method is provided in one example and includes receiving data propagating in a network environment, and identifying selected words within the data based on a whitelist. The whitelist includes a plurality of designated words to be tagged. The method further includes assigning a weight to the selected words based on at least one characteristic associated with the data, and associating the selected words to an individual. A resultant composite is generated for the selected words that are tagged. In more specific embodiments, the resultant composite is partitioned amongst a plurality of individuals associated with the data propagating in the network environment. A social graph can be generated that identifies a relationship between a selected individual and the plurality of individuals based on a plurality of words exchanged between the selected individual and the plurality of individuals.
    • 在一个示例中提供了一种方法,并且包括接收在网络环境中传播的数据,以及基于白名单来识别数据内的所选择的单词。 白名单包括要标记的多个指定单词。 所述方法还包括基于与所述数据相关联的至少一个特性来分配对所选择的单词的权重,以及将所选择的单词与个人相关联。 为所标记的所选择的单词生成结果复合。 在更具体的实施例中,所得到的复合物在与在网络环境中传播的数据相关联的多个个体之间被划分。 可以生成基于在所选择的个体与多个个体之间交换的多个单词来识别所选个体与多个个体之间的关系的社交图。