Two-level DP-matching--A dynamic programming-based pattern matching algorithm for connected word recognition
Two-level DP-matching--A dynamic programming-based pattern matching algorithm for connected word recognition
复制标题
两级DP匹配——一种基于动态规划的连词识别模式匹配算法
DOI：
10.1109/tassp.1979.1163310
复制
发表时间：
1979
期刊：
影响因子：
--
通讯作者：
H. Sakoe
中科院分区：
文献类型：
--
作者：
H. Sakoe
本文报告了一种用于连接词识别的模式匹配方法。首先，给出了基于未知连续语音和人工合成的连接参考模式之间的模式匹配的连接词识别的一般原理。通过使用基于动态编程的时间扭曲技术（DP 匹配），可以实现时间归一化功能。然后，结果表明，通过将匹配过程分为两个步骤，可以有效地进行匹配过程。所导出的算法被广泛地进行了识别实验。一项针对说话者的识别实验表明，五个人连续说出的数字数据（一到四位数字）的识别准确率高达 99.6%。计算时间和内存需求均被证明在合理的范围内。
This paper reports a pattern matching approach to connected word recognition. First, a general principle of connected word recognition is given based on pattern matching between unknown continuous speech and artificially synthesized connected reference patterns. Time-normalization capability is allowed by use of dynamic programming-based time-warping technique (DP-matching). Then, it is shown that the matching process is efficiently carried out by breaking it down into two steps. The derived algorithm is extensively subjected to recognition experiments. It is shown in a talker-adapted recognition experiment that digit data (one to four digits) connectedly spoken by five persons are recognized with as high as 99.6 percent accuracy. Computation time and memory requirement are both proved to be within reasonable limits.