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    • 27. 发明授权
    • Enhanced likelihood computation using regression in a speech recognition system
    • 在语音识别系统中使用回归来增强似然计算
    • US06493667B1
    • 2002-12-10
    • US09368669
    • 1999-08-05
    • Peter V. de SouzaYuqing GaoMichael PichenyBhuvana Ramabhadran
    • Peter V. de SouzaYuqing GaoMichael PichenyBhuvana Ramabhadran
    • G10L1514
    • G10L15/144G10L2015/085
    • In order to achieve low error rates in a speech recognition system, for example, in a system employing rank-based decoding, we discriminate the most confusable incorrect leaves from the correct leaf by lowering their ranks. That is, we increase the likelihood of the correct leaf of a frame, while decreasing the likelihoods of the confusable leaves. In order to do this, we use the auxiliary information from the prediction of the neighboring frames to augment the likelihood computation of the current frame. We then use the residual errors in the predictions of neighboring frames to discriminate between the correct (best) and incorrect leaves of a given frame. We present a new methodology that incorporates prediction error likelihoods into the overall likelihood computation to improve the rank position of the correct leaf.
    • 为了在语音识别系统中实现低错误率,例如,在采用基于秩解码的系统中,我们通过降低他们的等级来区分来自正确叶片的最混淆的不正确的叶子。 也就是说,我们增加了一帧正确叶片的可能性,同时降低了可疑叶片的可能性。 为了做到这一点,我们使用来自相邻帧的预测的辅助信息来增加当前帧的似然性计算。 然后,我们使用相邻帧的预测中的残差来区分给定帧的正确(最佳)和不正确的叶。 我们提出一种将预测误差可能性纳入总体似然计算的新方法,以提高正确叶子的排名。
    • 30. 发明授权
    • Enhanced linguistic transformation
    • 加强语言转型
    • US07881928B2
    • 2011-02-01
    • US11680863
    • 2007-03-01
    • Yuqing GaoLiang GuWei Zhang
    • Yuqing GaoLiang GuWei Zhang
    • G10L15/00
    • G06F17/28G10L15/22G10L21/06
    • Techniques for enhanced linguistic transformation are disclosed. For example, a method of linguistic transformation includes the steps of providing at least one input to a plurality of modules, wherein at least one module has a different configuration than at least another module, obtaining at least one output from each of at least a subset of the plurality of modules, and generating a set of distinct outputs. The input and the output include linguistic representations and at least a portion of the output is a result of applying one or more linguistic transformations to at least a portion of the input.Techniques for displaying a plurality of results so as to emphasize component-level differences are also disclosed. By way of example, a method of displaying a plurality of results includes the steps of determining at least one primary result within the plurality of results; displaying the at least one primary result with at least a first set of color attributes; and displaying at least one alternative result with at least a second set of color attributes. Each result represents an application of at least one linguistic transformation to a common input and each result comprises a plurality of components.
    • 公开了增强语言转型的技术。 例如,语言转换的方法包括向多个模块提供至少一个输入的步骤,其中至少一个模块具有与至少另一个模块不同的配置,从至少一个子集中的每一个获得至少一个输出 并且生成一组不同的输出。 输入和输出包括语言表示,并且输出的至少一部分是将一个或多个语言变换应用于输入的至少一部分的结果。 还公开了用于显示多个结果以强调组件级别差异的技术。 作为示例,显示多个结果的方法包括确定多个结果内的至少一个主要结果的步骤; 用至少第一组颜色属性显示所述至少一个主要结果; 以及至少显示具有至少第二组颜色属性的替代结果。 每个结果表示对公共输入的至少一个语言变换的应用,并且每个结果包括多个分量。