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2. 发明授权

US06850888B1 Methods and apparatus for training a pattern recognition system using maximal rank likelihood as an optimization function 失效
标题翻译：使用最大秩可能性作为优化函数训练模式识别系统的方法和装置
公开(公告)号：US06850888B1
公开(公告)日：2005-02-01
申请号：US09680706
申请日：2000-10-06
申请人： Yuqing Gao , Yongxin Li , Michael Alan Picheny
发明人： Yuqing Gao , Yongxin Li , Michael Alan Picheny
IPC分类号： G10L15/14 , G10L15/00
CPC分类号： G10L15/144
摘要： A method and apparatus are disclosed for training a pattern recognition system, such as a speech recognition system, using an improved objective function. The concept of rank likelihood, previously applied only to the decding process, is applied in a novel manner to the parameter estimation of the training phase of a pattern recognition system. The disclosed objective function is based on a pseudo-rank likelihood that not only maximizes the likelihood of an observation for the correct class, but also minimizes the likelihoods of the observation for all other classes, such that the discrimination between classes is maximized. A training process is disclosed that utilizes the pseudo-rank likelihood objective function to identify model parameters that will result in a pattern recognizer with the lowest possible recognition error rate. The discrete nature of the rank-based rank likelihood objective function is transformed to allow the parameter estimations to be optimized during the training phase.
摘要翻译：公开了一种使用改进的目标函数来训练诸如语音识别系统的模式识别系统的方法和装置。先前仅适用于解码处理的等级似然性的概念以新颖的方式应用于模式识别系统的训练阶段的参数估计。所公开的目标函数基于伪秩可能性，其不仅使对正确类的观察的可能性最大化，而且使对所有其他类的观察的可能性最小化，使得类之间的区分最大化。公开了一种训练过程，其利用伪秩似然度目标函数来识别将产生具有最低可能识别错误率的模式识别器的模型参数。转换基于秩的等级似然目标函数的离散性质，以便在训练阶段优化参数估计。

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