公开(公告)号：US07454341B1

公开(公告)日：2008-11-18

申请号：US10148028

申请日：2000-09-30

申请人： Jielin Pan ,  Baosheng Yuan

发明人： Jielin Pan ,  Baosheng Yuan

IPC分类号： G10L15/14

CPC分类号： G06K9/6223 ,  G10L15/063 ,  G10L2015/0631

摘要： According to one aspect of the invention, a method is provided in which a mean vector set and a variance vector set of a set of N Gaussians are divided into multiple mean sub-vector sets and variance sub-vector sets, respectively. Each mean sub-vector set contains a subset of the dimensions of the corresponding mean vector set and each variance sub-vector set contains a subset of the dimensions of the corresponding variance vector set. Each resultant sub-vector set is clustered to build a codebook for the respective sub-vector set using a modified K-means clustering process which dynamically merges and splits clusters based upon the size and average distortion of each cluster during each iteration in the modified K-means clustering process.

摘要翻译： 根据本发明的一个方面，提供了一种方法，其中将一组N高斯的均值向量集和方差矢量集分别分成多个平均子向量集和方差子向量集。 每个平均子向量集包含对应的平均向量集的维度的子集，并且每个方差子向量集合包含相应方差向量集合的维度的子集。 每个合成的子向量集合被聚类以使用修改的K均值聚类过程来构建用于相应子向量集的码本，其基于在修改的K中的每个迭代期间每个簇的大小和平均失真来动态地合并和分割聚类 - 聚类过程。

公开(公告)号：US07418386B2

公开(公告)日：2008-08-26

申请号：US10297354

申请日：2001-04-03

申请人： Chunrong Lai ,  Qingwei Zhao ,  Jielin Pan

发明人： Chunrong Lai ,  Qingwei Zhao ,  Jielin Pan

IPC分类号： G10L15/18 ,  G06F17/20

CPC分类号： G10L15/197 ,  G10L15/06

摘要： According to one aspect of the invention, a method is provided in which a set of probabilistic attributes in an N-gram language model is classified into a plurality of classes. Each resultant class is clustered into a plurality of segments to build a code-book for the respective class using a modified K-means clustering process which dynamically adjusts the size and centroid of each segment during each iteration in the modified K-means clustering process. A probabilistic attribute in each class is then represented by the centroid of the corresponding segment to which the respective probabilistic attribute belongs.

摘要翻译： 根据本发明的一个方面，提供了一种将N-gram语言模型中的一组概率属性分类为多个类的方法。 每个结果类被聚集成多个段以使用修改的K均值聚类过程为相应类构建代码簿，其在修改的K均值聚类处理中的每次迭代期间动态地调整每个段的大小和质心。 然后，每个类中的概率属性由相应概率属性所属的对应段的质心表示。

公开(公告)号：US20060053015A1

公开(公告)日：2006-03-09

申请号：US10297354

申请日：2001-04-03

申请人： Chunrong Lai ,  Qingwei Zhao ,  Jielin Pan

发明人： Chunrong Lai ,  Qingwei Zhao ,  Jielin Pan

IPC分类号： G10L15/18

CPC分类号： G10L15/197 ,  G10L15/06

摘要： According to one aspect of the invention, a method is provided in which a set of probabilistic attributes in an N-gram language model is classified into a plurality of classes. Each resultant class is clustered into a plurality of segments to build a code-book for the respective class using a modified K-means clustering process which dynamically adjusts the size and centroid of each segment during each iteration in the modified K-means clustering process. A probabilistic attribute in each class is then represented by the centroid of the corresponding segment to which the respective probabilistic attribute belongs.

摘要翻译： 根据本发明的一个方面，提供了一种将N-gram语言模型中的一组概率属性分类为多个类的方法。 每个结果类被聚集成多个段以使用修改的K均值聚类过程为相应类构建代码簿，其在修改的K均值聚类处理中的每次迭代期间动态地调整每个段的大小和质心。 然后，每个类中的概率属性由相应概率属性所属的对应段的质心表示。