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    • 22. 发明授权
    • System operable as an automaton for recognizing continuously spoken
words with reference to demi-word pair reference patterns
    • 可用作自动机的系统,用于识别连续口头词,参考二字对对参考模式
    • US4513435A
    • 1985-04-23
    • US370637
    • 1982-04-21
    • Hiroaki SakoeSeibi Chiba
    • Hiroaki SakoeSeibi Chiba
    • G10L11/00G10L15/00G10L15/10G10L1/00
    • G10L15/00
    • A system for recognizing a continuously spoken word sequence with reference to preselected reference words with the problem of coarticulation removed, comprises a pattern memory for memorizing demi-word pair reference patterns consisting of a former and a latter reference pattern segment for each reference word and a word pair reference pattern segment for each permutation with repetition of two words selected from the preselected reference words. A recognition unit is operable as a finite-state automaton on concatenating the demi-word pair reference patterns so that no contradiction occurs at each interface of the reference patterns in every concatenation. It is possible to use the automaton in restricting the number of reference patterns in each concatenation either to an odd or an even positive integer.
    • 一种用于识别连续口语单词序列的系统,涉及去除了coarticulation问题的预先选择的参考词,包括用于存储由每个参考单词的前一个和后一个参考图形段组成的单词对参考模式的模式存储器,以及 用于每次排列的字对参考图案片段,其中重复从预选参考词中选择的两个词。 一个识别单元可以作为有限状态自动机来连接这个二字对对参考图案,使得在每个级联中的参考图形的每个界面处不发生矛盾。 可以使用自动机将每个级联中的参考模式的数量限制为奇数或偶数正整数。
    • 23. 发明授权
    • Pattern recognition with a warping function decided for each reference
pattern by the use of feature vector components of a few channels
    • 通过使用几个通道的特征向量分量,对每个参考模式决定了具有翘曲函数的模式识别
    • US4282403A
    • 1981-08-04
    • US64965
    • 1979-08-08
    • Hiroaki Sakoe
    • Hiroaki Sakoe
    • G10L11/00G06K9/62G06K9/64G06T1/00G10L15/00G10L15/12G10L1/00
    • G10L15/12G06K9/6206G10L15/00
    • In a pattern recognition device according to pattern matching, one or more specific dimensions of vector components are memorized for each reference pattern feature vector sequence in a reference pattern memory for the reference pattern feature vector sequences. A warping function for time-normalizing input pattern feature vectors of a sequence and the vectors of each reference pattern feature vector sequence is determined so as to minimize the difference between a pattern represented by the specific vector components of the specific dimension or dimensions and another pattern represented by the vector components corresponding in the input pattern feature vector sequence to the specific reference pattern feature vector components as regards the dimensions of a space in which each input or reference pattern feature vector is defined. The input pattern feature vector sequence and each reference pattern feature vector sequence are subjected to nonlinear pattern matching with reference to the warping function. The pattern matching may be between the vector components of all dimensions or those of several dimensions including the specific dimension or dimensions. Preferably, one or more dimensions are specified as the specific one or ones by selecting each dimension for which a variation with time of a pattern represented by the reference pattern feature vector components is a maximum of similar variations of patterns represented by the vector components of other dimensions.
    • 在根据图案匹配的图案识别装置中,针对参考图案特征向量序列的参考图案存储器中的每个参考图案特征向量序列存储矢量分量的一个或多个特定维度。 确定用于对序列的输入模式特征向量进行时间归一化和每个参考模式特征向量序列的向量的变形函数,以使由特定维度或维度的特定向量分量表示的模式与另一模式之间的差异最小化 由输入图形特征向量序列中对应的矢量分量表示为与定义每个输入或参考图案特征向量的空间的尺寸相对于特定参考图案特征向量分量。 输入图形特征向量序列和每个参考图形特征向量序列参照扭曲函数进行非线性模式匹配。 图案匹配可以在所有尺寸的矢量分量或包括特定尺寸或尺寸的几个维度的矢量分量之间。 优选地,一个或多个维度被指定为特定的一个或多个维度,通过选择其中由参考图案特征向量分量表示的图案随时间变化的变化是由其他的矢量分量表示的图案的相似变化的最大值 尺寸。