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- W2262298155 abstract "在语音的决定，树基于州的系住，有改变叶节点的决定树与不同复杂性表示模型。由在系统性能和扬声器改编上学习模型复杂性的影响，一棵决定树动态修剪方法基于最小的描述，长度(MDL ) 标准被介绍。在方法，当一个起始的模型集合，和模型复杂性被增加根据改编数据的数量改变的一个惩罚参数计算，一棵训练得好的、大尺寸的语音的决定树被选择。大部分归因于起始的模型的合理选择和集成 MDL 标准随机、固定，由与说话者改编结合的建议方法获得高效。" @default.
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- W2262298155 date "2006-01-01" @default.
- W2262298155 modified "2023-09-24" @default.
- W2262298155 title "Minimum description length criterion based decision tree dynamic pruning method in speech recognition" @default.
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