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Combined quantized and continuous feature vector HMM approach to speech recognition

机译:结合量化和连续特征向量HMM的语音识别方法

摘要

A device capable of achieving recognition at a high accuracy and with fewer calculations and which utilizes an HMM. The present device has a vector quantizing circuit generating a model by quantizing vectors of a training pattern having a vector series, and converting the vectors into a label series of clusters to which they belong, a continuous distribution probability density HMM generating circuit for generating a continuous distribution probability density HMM from a quantized vector series corresponding to each label of the label series, and a label incidence calculating circuit for calculating the incidence of the labels in each state from the training vectors classified in the same clusters and the continuous distribution probability density HMM.
机译:使用HMM的设备能够以较高的准确度和较少的计算来实现识别。本装置具有:矢量量化电路,其通过对具有矢量序列的训练模式的矢量进行量化,并将其转换成它们所属的簇的标签序列,来生成模型;以及连续分布概率密度HMM生成电路,用于生成连续的来自与标签系列的每个标签相对应的量化矢量系列的分布概率密度HMM,以及标签发生率计算电路,该标签发生率计算电路用于根据分类为相同簇的训练矢量和连续分布概率密度HMM计算每种状态下标签的发生率。

著录项

  • 公开/公告号US6434522B1

    专利类型

  • 公开/公告日2002-08-13

    原文格式PDF

  • 申请/专利权人 TSUBOKA EIICHI;

    申请/专利号US19970864460

  • 发明设计人 EIICHI TSUBOKA;

    申请日1997-05-28

  • 分类号G10L151/40;

  • 国家 US

  • 入库时间 2022-08-22 00:49:50

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