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Method of refining statistical pattern recognition models and statistical pattern recognizers

机译:精炼统计模式识别模型的方法和统计模式识别器

摘要

A device (800) performs statistical pattern recognition using model parameters that are refined by optimizing an objective function that includes a term for many items of training data for which recognition errors occur wherein each term depends on a relative magnitude of a first score for a recognition result for an item of training data and a second score calculated by evaluating a statistical pattern recognition model identified by a transcribed identity of the training data item with feature vectors extracted from the item of training data. The objective function does not include terms for items of training data for which there is a gross discrepancy between a transcribed identity and a recognized identity. Gross discrepancies can be detected by probability score or pattern identity comparisons. Terms, of the objective function are weighted based on the type of recognition error and weights can be increased for high priority patterns.
机译:设备( 800 )使用模型参数执行统计模式识别,该模型参数通过优化目标函数来优化,该目标函数包括许多项训练数据项的项,这些项发生识别错误,其中每项项都取决于相对幅度用于训练数据项的识别结果的第一分数和通过评估统计模式识别模型计算出的第二分数,该统计模式识别模型是利用从训练数据项提取的特征向量来评估训练数据项的转录身份所标识的。目标函数不包括训练数据项的术语,在这些术语中,转录的身份和公认的身份之间存在重大差异。总体差异可以通过概率得分或模式身份比较来检测。根据识别错误的类型对目标函数的项进行加权,对于高优先级模式,可以增加权重。

著录项

  • 公开/公告号US2006136205A1

    专利类型

  • 公开/公告日2006-06-22

    原文格式PDF

  • 申请/专利权人 JIANMING J. SONG;

    申请/专利号US20040018271

  • 发明设计人 JIANMING J. SONG;

    申请日2004-12-21

  • 分类号G10L15/06;

  • 国家 US

  • 入库时间 2022-08-21 21:47:23

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