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Short note on two output-dependent hidden Markov models

机译:关于两个依赖于输出的隐藏Markov模型的简短说明

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The purpose of this note is to study the assumption of "mutual information independence", which is used by Zhou [Zhou, G.D., 2005. Direct modelling of output context dependence in discriminative hidden Markov model. Pattern Recognition Lett. 26 (5), 545-553] for deriving an output-dependent hidden Markov model, the so-called discriminative HMM (D-HMM), in the context of determining a stochastic optimal sequence of hidden states. The assumption is extended to derive its generative counterpart, the G-HMM. In addition, state-dependent representations for two output-dependent HMMs, namely HMMSDO [Li, Y., 2005. Hidden Markov models with states depending on observations. Pattern Recognition Lett. 26 (7), 977-984] and D-HMM, are presented.
机译:本注释的目的是研究“相互信息独立”的假设,该假设由Zhou [Zhou,G.D.,2005使用。在判别式隐马尔可夫模型中对输出上下文的依赖性进行直接建模。模式识别字母。参见图26(5),545-553],在确定隐藏状态的随机最优序列的情况下,用于导出依赖输出的隐马尔可夫模型,即所谓的判别HMM(D-HMM)。扩展该假设以推导其生成的对应物G-HMM。另外,两个输出相关的HMM的状态相关表示,即HMMSDO [Li,Y.,2005。状态的隐马尔可夫模型取决于观察。模式识别字母。 26(7),977-984]和D-HMM。

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